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Selected AbstractsMarketing Category Forecasting: An Alternative of BVAR-Artificial Neural Networks¶DECISION SCIENCES, Issue 4 2000James J. Jiang ABSTRACT Analyzing scanner data in brand management activities presents unique difficulties due to the vast quantity of the data. Time series methods that are able to handle the volume effectively often are inappropriate due to the violation of many statistical assumptions in the data characteristics. We examine scanner data sets for three brand categories and examine properties associated with many time series forecasting methods. Many violations are found with respect to linearity, normality, autocorrelation, and heteroscedasticity. With this in mind we compare the forecasting ability of neural networks that require no assumptions to two of the more robust time series techniques. Neural networks provide similar forecasts to Bayesian vector autoregression (BVAR), and both outperform generalized autoregressive conditional herteroscedasticty (GARCH) models. [source] Multicriteria maximum likelihood neural network approach to positron emission tomographyINTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, Issue 6 2000Yuanmei Wang Abstract The emerging technology of positron emission image reconstruction is introduced in this paper as a multicriteria optimization problem. We show how selected families of objective functions may be used to reconstruct positron emission images. We develop a novel neural network approach to positron emission imaging problems. We also studied the most frequently used image reconstruction methods, namely, maximum likelihood under the framework of single performance criterion optimization. Finally, we introduced some of the results obtained by various reconstruction algorithms using computer-generated noisy projection data from a chest phantom and real positron emission tomography (PET) scanner data. Comparison of the reconstructed images indicated that the multicriteria optimization method gave the best in error, smoothness (suppression of noise), gray value resolution, and ghost-free images. © 2001 John Wiley & Sons, Inc. Int J Imaging Syst Technol 11, 361,364, 2000 [source] Creating cluster-specific purchase profiles from point-of-sale scanner data and geodemographic clusters: improving category management at a major US grocery chainJOURNAL OF CONSUMER BEHAVIOUR, Issue 2 2004Peter Duchessi Abstract In the retail grocery industry, category management is the process of managing categories of products for greater profitability and customer value. Category management is a data-driven process and, as a result, can benefit from point-of-sale (POS) scanner data. This paper describes the results of a one-year project that shows how to use POS scanner data and geodemographic clusters to improve the practice of category management at Price Chopper, a large US grocery chain. The paper demonstrates how to merge POS scanner data with geodemographic clusters to create detailed purchase profiles that provide valuable information to category managers. It also discusses the trials and tribulations of using scanner data and provides several findings as implications (eg store-specific promotions should be more effective than chain-wide promotions for stores servicing a small number of geodemographic clusters with distinct shopping profiles) that supermarket managers can immediately use to improve existing promotional strategies. The paper's contents should be relevant to academicians and practitioners interested in improving the practice of category management in the UK, USA, Western Europe and Australia. Copyright © 2004 Henry Stewart Publications. [source] Factors influencing olive oil brand choice in Spain: an empirical analysis using scanner dataAGRIBUSINESS : AN INTERNATIONAL JOURNAL, Issue 1 2009Juan C. Gįzquez-Abad Olive oil consumption is growing all around the world as a consequence of the extension of the Mediterranean diet. Because of limited production, pricing, promotions, and consumer-related variables are essential to explain olive oil consumer behavior. As a consequence of this increasing consumption, it is fundamental to analyze the main factors influencing consumers' olive oil choices for both brands and retailers to be able to compete more efficiently and satisfy consumer needs more closely. But, few such studies are concerned with olive oil (although a great many works in the literature analyze the influence of these factors in other product categories). In a sociocultural context like the Spanish market, in which brand awareness is strong and the use of the product is very high, these factors are even more important. Thus, the main objective of this article is to determine and assess how different marketing variables, such as price, price discounts, use of store flyers and loyalty, explain olive oil brand choice. [Econlit citations: M310, Q130]. © 2009 wiley Periodicals, Inc. [source] Do psychological prices contribute to price rigidity?AGRIBUSINESS : AN INTERNATIONAL JOURNAL, Issue 1 2006Evidence from German scanner data on food brands A substantial degree of price rigidity has been reported for branded foods in various studies with scanner data. One possible explanation for price rigidity is the existence of psychological pricing points. The authors analyze to what extent psychological pricing plays a role in grocery retailing and whether it contributes to the price rigidity of branded foods in Germany. Psychological pricing,defined here as just-below-the-round-figure-pricing,is empirically analyzed with scanner data of weekly prices for 20 food brands in 38 retail outlets from September 1996 to June 1999. Psychological pricing turned out to be extremely important in German food retailing. Branded food prices are remarkably sticky and psychological pricing points contribute strongly to price rigidity. Other factors like the sales phenomenon and firm-specific effects are additionally important. [EconLit Classifications: Q110, Q130]. © 2006 Wiley Periodicals, Inc. Agribusiness 22: 51,67, 2006. [source] Analyses of consumers' dietary behavior: An application of the AIDS model to supermarket scanner dataAGRIBUSINESS : AN INTERNATIONAL JOURNAL, Issue 2 2003Eugene Jones Nationwide food consumption surveys often find no difference in the diets of lower and higher income Americans, while studies of particular food commodities find major differences. These contrasting results represent a consumption paradox. We attempt to gain an understanding of this paradox by using supermarket scanner data to examine food purchases and, by extension, consumption patterns for consumers in two, geographically distinct, income areas. These areas are part of the larger Columbus, OH, metropolitan area (CMA) and six stores are selected for purchase and consumption analyses,three from the lowest income areas of the CMA and three from the highest income areas. Seven product categories are analyzed in this study and these categories are subdivided into meaningful nutritional classes. An Almost Ideal Demand System is employed and the empirical results reveal major differences in consumption behavior for the two groups. [EconLit citations: D120 and D190.] © 2003 Wiley Periodicals, Inc. Agribusiness 19: 203,221, 2003. [source] Estimating own and cross brand price elasticities, and price,cost margin ratios using store-level daily scanner dataAGRIBUSINESS : AN INTERNATIONAL JOURNAL, Issue 4 2001Junko Kinoshita This article addresses three issues related to Japanese dairy demand analysis. First, an econometric fluid milk demand model is estimated using store-level daily scanner data to determine whether the own-price elasticities are significantly different from previous estimates based on aggregate market-level data. This is important because of the current debate among Japanese dairy industry leaders concerning whether fluid milk is price inelastic or elastic. Own-price elasticity differences between fresh and reconstituted milk products are also examined. Second, milk product cross-price elasticities are estimated to measure the degree, if any, of substitutability between fresh milk and reconstituted milk products. Because most previous studies have relied upon aggregate market-level data, there are no previous estimates of cross-price elasticities for fresh milk and reconstituted milk products. Finally, price,cost margin ratios are estimated for each commodity using a method that does not require cost data, but rather relies on assumptions regarding the degree of competition to derive the price,cost margin ratio [Econlit alphanumeric subject codes: Q110, Q130]. © 2001 John Wiley & Sons, Inc. [source] The effects of informative and non-informative price patterns on consumer price judgmentsPSYCHOLOGY & MARKETING, Issue 6 2006Shai Danziger Converging evidence from laboratory experiments and empirical models of scanner data suggests that product price evaluations are often based on a comparison to an internal reference price. Research indicates that the reference price may reflect various characteristics of previously encountered prices including the mean, the range, and the last price encountered. In this research, the authors test whether, for prices purportedly sampled over time, the reference price reflects temporal patterns of the price sequence (ascending and descending prices). In four studies, participants viewed prices purportedly sampled at one time point or at multiple time points and then evaluated a target price. Price distributions differed only in their temporal pattern, whereas the mean, the range, and in some conditions, the last price, were held constant. The results reveal that the price pattern does not affect price judgments when prices are purportedly sampled at one time point. However, for ascending and descending price sequences purportedly sampled over time, the price pattern affects price judgments. Based on these findings the authors propose that consumers flexibly select the internal reference price used for price evaluations. © 2006 Wiley Periodicals, Inc. [source] Demand, Information, and Competition: Why Do Food Prices Fall at Seasonal Demand Peaks?THE JOURNAL OF INDUSTRIAL ECONOMICS, Issue 1 2000James M. MacDonald Prices for seasonal food products fall at demand peaks. Price declines are not driven by falling agricultural input prices; indeed, farm to retail margins narrow sharply. I use electronic scanner data from a sample of US supermarkets to show that seasonal price declines are closely linked to market concentration, and are much larger in markets with several rivals than where a single brand dominates. Seasonal demand increases reduce the effective costs of informative advertising, and increased informative advertising by retailers and manufacturers in turn may allow for increased market information and greater price sensitivity on the part of buyers. [source] Hedonic Price Indexes and the Matched Models ApproachTHE MANCHESTER SCHOOL, Issue 1 2004Mick Silver We consider three approaches to estimating quality-adjusted price changes: (i) the dummy variable approach from a hedonic regression, (ii) a superlative or exact hedonic index and (iii) a matching technique,a technique akin to that used by statistical offices. The dummy variable approach is prevalent in the literature and has been used for independent estimates of quality changes when commenting on sources of error in consumer price indexes. However, the availability of scanner data provides an opportunity to utilize data on the prices (unit values), volumes and quality characteristics of a much wider range of transactions and to consider methods less restrictive than the dummy variable approach. The practical use of superlative or exact hedonic index and matching techniques using scanner data is explored, and the results from all three methods are compared. A feature of the paper is the breadth of the empirical work. It not only encompasses three different approaches, but extends across four different types of consumer durables. The manner in which the three approaches relate to each other is explored and the implications for quality-adjusted price changes is discussed. [source] Sales and consumer inventoryTHE RAND JOURNAL OF ECONOMICS, Issue 3 2006Igal Hendel Temporary price reductions (sales) are common for many goods and naturally result in a large increase in the quantity sold. We explore whether the data support the hypothesis that these increases are, at least partly, due to demand anticipation: at low prices, consumers store for future consumption. This effect, if present, has broad economic implications. We test the predictions of an inventory model using scanner data with two years of household purchases. The results are consistent with an inventory model and suggest that static demand estimates may overestimate price sensitivity. [source] The diffusion of marketing science in the practitioners' community: opening the black boxAPPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 4-5 2005Albert C. Bemmaor Abstract This editorial discusses an illustration of the potential hindrances to the diffusion of modern methodologies in the practitioners' (i.e. the buyers of research, not the consultants) community. Taking the example of classical regression analysis based on store-level scanner data, the authors discuss the potential limitations of the classical regression model, with the example of the occurrence of ,wrong' signs and of coefficients with unexpected magnitudes. In an interview with one of the authors, a (randomly picked) Senior Marketing Research Manager at a leading firm of packaged goods reports his/her experience with econometric models. To him/her, econometric models are presented as a ,black box' (his/her written words). In his/her experience, they provided results that were ,quite good' in a ,much focused' context only. There were experimental data obtained with a Latin square design and the analysis included a single brand with only four stock-keeping units (SKUs). The company ,dropped' the more ,ambitious' studies, which analysed the effect of the retail promotions run by all the actors in a market because of a lack of predictive accuracy (his/her written words are in quotes). The authors suggest that Bayesian methodology can help open the black box and obtain more acceptable results than those obtained at present. Copyright © 2005 John Wiley & Sons, Ltd. [source] | ||||||||||