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Regression modelBehavioral pricing / scanner-data choice models

Reference Price Modeling

Reference price models capture the behavioral reality that consumers judge a price not in absolute terms but relative to an internal benchmark — a reference price they have formed from past prices. When the observed price falls below the reference the shopper perceives a gain; when it rises above, a loss, an unpleasant 'sticker shock.' Drawing on prospect theory, these models enter gains and losses as separate terms and let losses weigh more heavily than equivalent gains, an asymmetry known as loss aversion. Kalyanaram and Winer's 1995 synthesis crystallized three robust empirical generalizations: consumers use reference prices, they form them largely from past prices, and they respond more strongly to losses than to gains. The reference price itself is usually constructed by exponentially smoothing past prices, the same smoothing logic Guadagni and Little used to build loyalty variables, and the gain and loss terms are embedded in a brand-choice logit or demand model estimated on scanner panel data. The result is a richer, behaviorally grounded picture of how price changes move demand than a single symmetric price coefficient allows.

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来源

  1. Kalyanaram, G., & Winer, R. S. (1995). Empirical Generalizations from Reference Price Research. Marketing Science, 14(3 Supplement), G161-G169. DOI: 10.1287/mksc.14.3.G161
  2. Guadagni, P. M., & Little, J. D. C. (1983). A Logit Model of Brand Choice Calibrated on Scanner Data. Marketing Science, 2(3), 203-238. DOI: 10.1287/mksc.2.3.203

如何引用本页

ScholarGate. (2026, June 23). Reference Price Models (Asymmetric Gain-Loss Response). ScholarGate. https://scholargate.app/zh/marketing/reference-price-modeling

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ScholarGateReference Price Modeling (Reference Price Models (Asymmetric Gain-Loss Response)). 于 2026-06-24 检索自 https://scholargate.app/zh/marketing/reference-price-modeling · 数据集: https://doi.org/10.5281/zenodo.20539026