Santiago L. Rovere

Exploring associations between micro-level models of innovation diffusion and emerging macro-level adoption patterns

A micro-level agent-based model of innovation diffusion was developed that explicitly combines (a) an individual’s perception of the advantages or relative utility derived from adoption, and (b) social influence from members of the individual’s social network. The micro-model was used to simulate macro-level diffusion patterns emerging from different configurations of micro-model parameters. Micro-level simulation results matched very closely the adoption patterns predicted by the widely-used Bass macro-level model (Bass, 1969 [1]). For a portion of the p−q domain, results from micro-simulations were consistent with aggregate-level adoption patterns reported in the literature. Induced Bass macro-level parameters p and q responded to changes in micro-parameters: (1) p increased with the number of innovators and with the rate at which innovators are introduced; (2) q increased with the probability of rewiring in small-world networks, as the characteristic path length decreases; and (3) an increase in the overall perceived utility of an innovation caused a corresponding increase in induced p and q values. Understanding micro to macro linkages can inform the design and assessment of marketing interventions on micro-variables–or processes related to them–to enhance adoption of future products or technologies.

Simulating agricultural land rental markets by combining agent-based models with traditional economics concepts

Land exchange through rental transactions is a central process in agricultural systems. The land tenure regimes emerge from land transactions and structural and land use changes are tied to the dynamics of the land market. We introduce LARMA, a LAnd Rental MArket model embedded within the Pampas Model (PM), an agent-based model of Argentinean agricultural systems. LARMA produces endogenous formation of land rental prices. LARMA relies on traditional economic concepts for LRP formation but addresses some drawbacks of this approach by being integrated into an agent-based model that considers heterogeneous agents interacting with one another. PM-LARMA successfully reproduced the agricultural land tenure regimes and land rental prices observed in the Pampas. Including adaptive, heterogeneous and interacting agents was critical to this success. We conclude that agent-based and traditional economic models can be successfully combined to capture complex emergent land tenure and market price patterns while simplifying the overall model design. LARMA is a land rental market model with endogenous rental price formation.LARMA is embedded into the Pampas agent-based model (PM).LARMA combines traditional economics concepts with agent-based modeling.PM-LARMA successfully reproduces land tenure patterns and rental price dynamics.We discuss the advantages of combining approaches for modeling land rental markets.

Diffusion of two brands in competition: Cross-brand effect

We study the equilibrium points of a system of equations corresponding to a Bass based model that describes the diffusion of two brands in competition. To increase the understanding of the effects of the cross-brand parameters, we perform a sensitivity analysis. Finally, we show a comparison with an agent-based model inspired in the Potts model. Conclusions include that both models give the same diffusion curves only when the cross coefficients are not null.

Practical Points for the Software Development of an Agent-Based Model of a Coupled Human-Natural System

Modeling complex natural and human systems to support policy or management decision making is becoming increasingly common. The resulting models are often designed and implemented by researchers or domain experts with limited software engineering expertise. To help this important audience, we present our experience and share lessons learned from the design and implementation of an agent-based model of agricultural production systems in the Argentine Pampas, emphasizing the software engineering perspective. We discuss the models design including the model classes; the activity diagram, and data flow; the package and folder layout; the use of design patterns; performance optimization; initialization approaches; the analysis of results; and model measurement, validation, and verification.

A linked modelling framework to explore interactions among climate, soil water, and land use decisions in the Argentine Pampas

Abstract In flat environments, groundwater is relatively shallow, tightly associated with surface water and climate, and can have either positive and negative impacts on natural and human systems depending on its depth. A linked modelling and analysis framework that seeks to capture linkages across multiple scales at the climate/water/crop nexus in the Argentine Pampas is presented. This region shows a strong coupling between climate, soil water, and land use due to its extremely flat topography and poorly developed drainage networks. The work describes the components of the framework and, subsequently, presents results from simulations performed with the twin goals of (i) validating the framework as a whole and (ii) demonstrating its usefulness to explore interesting contexts such as unexperienced climate scenarios (wet/dry periods), hypothetical policies (e.g., differential grains export taxes), and adoption of non-structural technologies (e.g., cover crops) to manage water table depth.