The research, led by Riska Tiasmalomo and an interdisciplinary team of Indonesian agricultural scientists, takes aim at a persistent blind spot in agricultural sustainability research. Most previous studies of cut flower farming have examined only one or two dimensions at a time, such as profitability or plant physiology, using conventional statistical tools like regression analysis and analysis of variance. The team instead embraced system dynamics, a modeling technique pioneered by MIT engineer Jay Forrester, which is designed to capture the feedback loops, delays, and nonlinear interactions that make real-world systems so difficult to predict. Their framework integrates four dimensions simultaneously: economy, social conditions, technology and innovation, and ecology, a combination the authors abbreviate as ESTIE and anchor in the United Nations Sustainable Development Goals.

At the core of the modeling effort are 54 variables drawn from official statistics compiled by Batu City’s Central Statistics Agency and its Agriculture and Food Security Agency. The researchers first built a causal loop diagram, a conceptual map in which arrows show whether one variable strengthens or weakens another. They then translated this map into a stock and flow diagram using the Vensim PLE software, converting qualitative relationships into quantitative equations that could be simulated over a 15-year horizon from 2020 to 2035. Each of the four submodels centers on a single crucial variable: profit for the economy, the total number of farmers for the social dimension, agricultural tools and machinery for technology, and total rose production for ecology.

The economic submodel treats profit as a stock that fills with income and drains with expenditure. Income depends on production volume multiplied by price, while expenditure combines fixed costs, including land rent, taxes, and equipment depreciation, with variable costs such as seeds, fertilizer, pesticides, and labor. The numbers are striking: pesticide costs alone run between roughly 87 and 94 million Indonesian rupiah per hectare per year, and seed costs between 43 and 53 million. Because these inputs consume such a large share of revenue, even modest changes in input prices or selling prices ripple powerfully through the system, a dynamic the simulations make vividly clear.

The social submodel captures a quieter but equally threatening trend: farmers leaving the profession. Batu City counts 9,707 farmers overall, but only 279 of them grow cut roses, organized into 22 farmer groups and a single association. The model tracks an occupational transition of roughly 2,000 to 2,200 people per year, driven by the harsh arithmetic of farming that no longer meets daily needs. When farmers sell their land and move into manufacturing or service jobs, agricultural land is converted to other uses, which in turn pushes remaining farmers to seek better-paying work elsewhere. The researchers describe this as a self-reinforcing spiral in which land conversion and farmer attrition feed each other, eroding the industry’s foundations year after year.

Ecological pressures compound the problem. Agricultural land in Batu City is being converted to non-agricultural uses at a rate of 5 to 10 percent annually, driven by population growth, housing demand, and a booming tourism industry that needs hotels, supermarkets, and infrastructure. Meanwhile, rose production is buffeted by climate anomalies, modeled through temperature, humidity, rainfall, and rainy days, and by pest and disease attacks that the model allows to range from 15 to 50 percent of output. The technology submodel reveals its own paradox: of nearly 48,000 agricultural tools and machines in the city, more than 2,100 sit idle, often because subsidies arrived without repair facilities, spare parts, or training, leaving equipment damaged and unused.

To ensure the model faithfully reflected reality, the team subjected it to behavioral validation, comparing simulated outputs against historical data using two statistical tests: a comparison of averages, which must deviate by no more than 5 percent, and a comparison of amplitude variation, which must stay within 30 percent. All four submodels passed comfortably. The economic model’s error was just 3 percent, the social model 1.74 percent, the technology model 2.35 percent, and the ecological model 0.81 percent, indicating that the simulations track the actual behavior of Batu’s rose system with remarkable precision.

With a validated model in hand, the researchers ran three parameter scenarios, pessimistic, moderate, and optimistic, by adjusting key variables and projecting outcomes to 2035. The optimistic scenario emerged as the clear winner across every dimension. Economically, it requires raising the selling price of cut roses by 795 rupiah per stalk, from 788, while cutting fertilizer costs by about 33.5 million rupiah per year and pesticide costs by roughly 93 million rupiah per year. Under these conditions, profit in 2026 would climb to 378.3 million rupiah per hectare, well above the actual figure of 357.8 million, and continue rising toward more than 1.1 billion rupiah by 2035.

The social and technological prescriptions are equally concrete. Cutting the number of farmers abandoning the profession to 1,734 people per year, expanding the ranks of rose farmers to 360, and doubling extension service visits from 12 to 24 times per year would lift the projected farming population to 55,735 people by 2026, exceeding the baseline of 53,218. On the technology front, increasing actively used machinery to 24,079 units, reducing idle equipment, and raising the share of farmer groups adopting agricultural technology from 48.96 percent to 51.50 percent would push the total tool count to 205,090 units by 2026. Ecologically, the optimistic scenario calls for expanding the rose harvest area by 545 hectares, planting an additional 54.5 million rose trees, and slashing pest and disease attacks from 40 percent to 8.6 percent, which would raise 2026 production to 124.2 million stalks.

The study’s authors are careful to frame these figures not as predictions but as strategic guidance, a rational benchmark against which farmers, extension workers, and policymakers can evaluate decisions. Their central message is that sustainability cannot be achieved by fixing one variable in isolation. Lowering pesticide costs, for instance, must be paired with better pest management so that production does not fall; retaining farmers requires both economic viability and stronger social support through training and counseling. By modeling the four dimensions together, the dynamic systems approach reveals trade-offs and synergies that single-factor analyses miss entirely. For a city whose identity and economy are intertwined with a single flower, the stakes could hardly be higher. The simulations suggest that with coordinated action on prices, inputs, technology adoption, land protection, and farmer welfare, Batu’s rose industry can not only recover from its 2020 shock but grow steadily for decades, offering a replicable template for sustainable horticulture across Indonesia and beyond.

Subject of Research: Dynamic systems modeling of sustainable cut rose farming in Batu City, Indonesia

Article Title: Model and scenario of sustainable cut rose farming development in Batu City: A dynamic system approach for Indonesia's cut rose center

Article References: Tiasmalomo, R., Salam, M., Iswoyo, H., Jamil, M. H., Tenriawaru, A. N., Dermawan, R., Kamarulzaman, N. H., Akhsan, Heliawaty, Fudjaja, L., Rahmadanih, Ridwan, M., Ali, H. N. B., & Syam, S. H. (2026). Model and scenario of sustainable cut rose farming development in Batu City: A dynamic system approach for Indonesia's cut rose center. Environmental and Sustainability Indicators, 32, Article 101533. https://doi.org/10.1016/j.indic.2026.101533

Image Credits: AI Generated

DOI: 10.1016/j.indic.2026.101533

Keywords: cut roses, system dynamics, sustainable agriculture, Batu City, Indonesia, horticulture, simulation modeling, farmer welfare, agricultural technology, land conversion, pest management, scenario analysis

The study, published in SSM – Population Health by a research team led by John Pastor Ansah of Case Western Reserve University and University Hospitals Medical Center, is among the first to model urban food access as a dynamic system rather than a static snapshot. Using a technique known as system dynamics modeling, the researchers built a mathematical representation of how household income, food prices, grocery store viability, emergency food networks, and demographic change interact and reinforce one another over time. The model was calibrated with data from the U.S. Census Bureau, County Health Rankings and Roadmaps, the U.S. Department of Agriculture, and Ohio state sources, then run forward across a thirty-year horizon from 2015 to 2045.

Cleveland offers a stark testing ground for such an analysis. With a poverty rate exceeding 30 percent, more than double the national average, it ranks among the poorest large cities in the United States. Roughly 10.2 percent of U.S. households experienced food insecurity in 2021, but rates are substantially higher among Black and Hispanic households, and post-industrial cities like Cleveland concentrate the structural conditions—segregation, disinvestment, retail decline—that make nutritious food scarce where it is needed most. In many neighborhoods, residents depend on convenience stores, dollar stores, and fast-food outlets offering calorie-dense but nutrient-poor products, a pattern linked to elevated rates of obesity, diabetes, and cardiovascular disease.

The model’s architecture reflects this reality. It tracks the city’s population as two shifting stocks: people with adequate access to healthy food and people with limited access. Flows between these states are governed by birth and death rates, net migration, and transition rates modulated by the quality of the food environment, nutrition education, and support from food banks and pantries. Beneath this demographic layer sits an economic engine: food affordability is modeled as the proportion of households spending no more than 12 percent of income on food, a threshold reflecting typical expenditure shares in high-income countries. Healthy food costs, calibrated from USDA data for an average family of 2.4 people, rise with inflation, while household income grows through wages and Supplemental Nutrition Assistance Program benefits distributed across twelve income groups.

The most provocative insight lies in a feedback loop connecting charity to decline. As food becomes less affordable, demand for food banks and pantries rises. But the model proposes that expanding free food distribution can erode the customer base of grocery stores selling healthy food, straining their finances and pushing them toward closure. Each closure lengthens the average distance residents must travel to reach fresh produce, deepening food insecurity and driving yet more reliance on emergency food. The model’s authors are careful to stress that food banks play a vital, even life-sustaining role in the short term; the danger emerges when charity operates as a substitute for structural income and market interventions rather than a complement to them.

Under the business-as-usual scenario, the projections are grim. The share of households spending 12 percent or less of income on food falls from 27.4 percent in 2025 to just 15.6 percent by 2045, while the city’s food environment index collapses by roughly 53 percent. Limited access to healthy food climbs from 7.3 percent of residents to 17.7 percent. Meanwhile, the availability of unhealthy food outlets rises from 48.5 percent to 61.7 percent, full-service grocery stores dwindle from 21 to 8, and food banks and pantries multiply from 151 to 273 as the emergency system strains to absorb escalating need.

The intervention scenarios reveal a clear hierarchy of effectiveness. Simply doubling food bank funding cuts limited access modestly, to 14.6 percent, but leaves affordability untouched and even accelerates the underlying deterioration: in that scenario, grocery stores fall to just 5 and unhealthy outlets reach 64.1 percent. SNAP Double Up programs, which match benefits when spent on fresh produce, barely move the needle at all. Retail-focused incentives—grants and low-interest loans to keep grocery stores open—perform better, nearly tripling the number of stores by 2045 and trimming limited access to 13.4 percent. But the transformative results come from income. A substantial income increase, modeled as a shift toward higher earnings through federal and state economic and educational policies, lifts affordability to 46.1 percent—a 195 percent improvement over the baseline—cuts limited access to 6.1 percent, and reverses the retail exodus.

Most striking of all is the comprehensive scenario combining income growth, SNAP Double Up, grocery store incentives, and food bank funding. Together these policies cut limited access to healthy food by 82 percent relative to the status quo, raise the food environment index by 242 percent, and push affordability to 44.7 percent. Grocery stores recover to 20, unhealthy outlets recede to 37.5 percent, and even the emergency food network contracts back toward 170 pantries, a sign that fewer residents need the safety net at all. No single intervention achieves anything close to this; the model suggests the reinforcing feedback loops that drive food insecurity can only be broken by attacking income, retail viability, and assistance simultaneously.

The findings carry weight well beyond Ohio. Roughly half of Cleveland households earn $40,000 or less annually, and two-thirds earn under $60,000, meaning food consumes a disproportionate share of family budgets even before shocks like inflation. The researchers argue that policies strengthening household purchasing power—wage growth, workforce development, and income supports, including evidence from programs like the Alaska Permanent Fund dividend and municipal guaranteed-income pilots—may be as important to food security as anything that happens within the food sector itself. Unconditional transfers may be particularly effective, they note, because they reduce the financial uncertainty that leads households facing what psychologists call extrinsic mortality risk to prioritize immediate survival over long-term health investments.

The authors caution that their results are scenario-based insights rather than forecasts, and that the intervention scenarios are stylized policy experiments, not predictions of specific programs’ real-world feasibility. The model treats food access at an aggregate level and does not yet disaggregate by race, neighborhood, or household type, though community stakeholders—including residents of affected neighborhoods—helped shape its structure through group model-building workshops held in November 2023 and February 2024. Future work, the team suggests, could combine system dynamics with microsimulation to capture how policies affect different socioeconomic groups. For now, the message is unambiguous: food banks feed Cleveland today, but only incomes, supported by a stable retail landscape, can feed it tomorrow.

Subject of Research: System dynamics modeling of urban access to healthy food in Cleveland, Ohio

Article Title: Modeling the Dynamics of Access to Healthy Food. The Case of Cleveland, Ohio

Article References: Ansah, J. P., Rua, R. S., Patki, A., Yamoah, O., & Rajagopalan, S. (2026). Modeling the Dynamics of Access to Healthy Food. The Case of Cleveland, Ohio. SSM – Population Health, Article 101964. https://doi.org/10.1016/j.ssmph.2026.101964

Image Credits: AI Generated

DOI: 10.1016/j.ssmph.2026.101964

Keywords: food insecurity, food deserts, system dynamics, Cleveland, food affordability, grocery stores, food banks, SNAP, health equity, simulation modeling, income policy, food environment