Dynamical Systems Models for Market Evolution: A Mechanistic Alternative to Autoregressive Methods

Fuente: arXiv
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Hauptverfasser: Komarla, Aparna, Hill, Max
Format: Preprint
Veröffentlicht: 2025
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author Komarla, Aparna
Hill, Max
author_facet Komarla, Aparna
Hill, Max
contents We present a novel approach to modeling market dynamics using ordinary differential equations that explicitly incorporates product competitiveness and consumer behavior. Our framework treats market segments as interacting populations in a dynamical system analogous to predator-prey models, where competitive advantages drive market share transitions through mechanistic modeling of market flows including new product adoption, refresh cycles, and obsolescence dynamics.
format Preprint
id arxiv_https___arxiv_org_abs_2510_06778
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Dynamical Systems Models for Market Evolution: A Mechanistic Alternative to Autoregressive Methods
Komarla, Aparna
Hill, Max
Dynamical Systems
Applications
We present a novel approach to modeling market dynamics using ordinary differential equations that explicitly incorporates product competitiveness and consumer behavior. Our framework treats market segments as interacting populations in a dynamical system analogous to predator-prey models, where competitive advantages drive market share transitions through mechanistic modeling of market flows including new product adoption, refresh cycles, and obsolescence dynamics.
title Dynamical Systems Models for Market Evolution: A Mechanistic Alternative to Autoregressive Methods
topic Dynamical Systems
Applications
url https://arxiv.org/abs/2510.06778