Bedarfsmodelle

Bedarfsmodelle are analytical representations that describe the relationship between the demand for a product or service and various influencing factors. In economics, they are used to predict how changes in price, income, or other variables affect consumer behaviour. Demand models can be deterministic or stochastic, and they often rely on empirical data to calibrate parameters.

Common types of Bedarfsmodelle include linear models, where demand changes proportionally with independent variables, and nonlinear models such as logistic or exponential functions that capture saturation effects. Elasticity models, which measure the percentage change in quantity demanded relative to a percentage change in price or income, are also widely applied. In marketing, conjoint analysis and choice modeling fall under this umbrella, providing insights into consumer preferences for product attributes.

The construction of a demand model typically follows data collection, model specification, estimation through regression or maximum likelihood techniques, and validation with out‑of‑sample tests. Accurate demand modelling is essential for optimal pricing, inventory management, production planning, and overall strategic decision‑making. It allows firms and policymakers to assess the impact of interventions such as taxes, subsidies, or regulatory changes.

In supply chain management, Bedarfsmodelle inform demand forecasting, which underpins stock levels and logistics decisions. The integration of machine learning methods has expanded the scope of demand modelling, enabling the incorporation of high‑dimensional data like social media sentiment and weather patterns. Consequently, demand models continue to evolve as a crucial tool for understanding market dynamics and guiding effective resource allocation.