Usporedite metode

	Reference Price Modeling	Scanner Panel Analysis
Područje	Marketing	Marketing
Obitelj	Regression model	Regression model
Godina nastanka	1995	1983
Tvorac	Gurumurthy Kalyanaram & Russell S. Winer (synthesis); prospect-theory pricing tradition	Peter M. Guadagni & John D. C. Little
Vrsta	Behavioral price-response model with reference dependence	Disaggregate multinomial-logit brand-choice model
Temeljni izvor	Kalyanaram, G., & Winer, R. S. (1995). Empirical Generalizations from Reference Price Research. Marketing Science, 14(3 Supplement), G161-G169.	Guadagni, P. M., & Little, J. D. C. (1983). A Logit Model of Brand Choice Calibrated on Scanner Data. Marketing Science, 2(3), 203-238.
Drugi nazivi	Reference Price Effects, Sticker-Shock Model, Asymmetric Price Response Model, Prospect-Theoretic Pricing Model	Scanner Panel Logit, Guadagni-Little Model, Household Panel Choice Model, Loyalty-Variable Logit
Srodne	3	3
Sažetak	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.	Scanner panel analysis models individual households' brand choices using the purchase histories captured by UPC scanner panels, in which the same households are tracked occasion by occasion with the brand chosen and the prices and promotions they faced. The defining method is Guadagni and Little's 1983 multinomial logit of brand choice, the first model to put scanner panel data to serious analytical use. Its signal innovation is the loyalty variable: an exponentially smoothed measure of each household's past brand purchases that enters the utility function and captures persistent brand preference and state dependence. Alongside loyalty, the model includes price, promotion, and brand intercepts, and yields the probability that a household buys each brand on a given occasion. From the fitted model one recovers price and promotion elasticities at the individual level and can simulate how marketing actions shift choices. The framework launched the modern era of disaggregate choice modeling and remains the reference point for scanner-based brand-choice analysis.