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Abstract Chasing behavior is an example of the anchoring and adjustment heuristic that occurs in many business contexts. In inventory management settings, decision makers often engage in demand chasing by adjusting order quantities toward recent demand observations. This can result in lower profit for the firm and increased variability across the supply chain. Prior research suggests that demand chasing can be measured by regression or correlation. Using two empirical datasets, we show that the observed costs associated with chasing are better captured using regression. We complement our empirical findings through comprehensive simulations across a range of order generating functions, supporting the robustness of regression models. Finally, we discuss behavioral differences between approaches and explain why certain models are better equipped for measuring demand chasing.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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