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Simulating spatial dynamics and processes in a retail gasoline market: An agent-based modeling approach

机译：在零售汽油市场中模拟空间动力学和过程：基于代理的建模方法

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摘要

Simulating the dynamics and processes within a spatially influenced retail market, such as the retail gasoline market, is a highly challenging research area. Current approaches are limited through their inability to model the impact of supplier or consumer behavior over both time and space. Agent-based models (ABMs) provide an alternative approach that overcomes these problems. We demonstrate how knowledge of retail pricing is extended by using a 'hybrid' model approach: an agent model for retailers and a spatial interaction model for consumers. This allows the issue of spatial competition between individual retailers to be examined in a way only accessible to agent-based models, allowing each model retailer autonomous control over optimizing their price. The hybrid model is shown to be successful at recreating spatial pricing dynamics at a national scale, simulating the effects of a rise in crude oil prices as well as accurately predicting which retailers were most susceptible to closure over a 10-year period.
机译：在一个受空间影响的零售市场（例如零售汽油市场）中模拟动态和过程是一个极富挑战性的研究领域。当前的方法由于无法建模供应商或消费者行为在时间和空间上的影响而受到限制。基于代理的模型（ABM）提供了克服这些问题的替代方法。我们演示了如何使用“混合”模型方法扩展零售定价的知识：零售商的代理商模型和消费者的空间互动模型。这允许以仅基于代理的模型可以访问的方式来检查各个零售商之间的空间竞争问题，从而允许每个模型零售商自主控制其价格的优化。事实证明，这种混合模型可以成功地在全国范围内重建空间价格动态，模拟原油价格上涨的影响，并准确预测哪些零售商在10年内最容易倒闭。

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