Scanner Data

Consumers in developed countries are increasingly interested in the consumption of products incorporating ethical aspects, particularly fair trade products. They are usually distributed in a network of World Shops and more recently also introduced in ...

The workhorse brand choice models in marketing are the multinomial logit (MNL) and nested multinomial logit (NMNL). These models place strong restrictions on how brand share and purchase incidence price elasticities are related. In this paper, we propose a new model of brand choice, the "price consideration" (PC) model, that allows more flexibility in this relationship. In the PC model, consumers do not observe prices in each period. Every week, a consumer decides whether to consider a category. Only then does he/she look at prices and decide whether and what to buy. Using scanner data, we show the PC model fits much better than MNL or NMNL. Simulations reveal the reason: the PC model provides a vastly superior fit to inter-purchase spells.

Food manufacturers have an incentive to include nutrient content claims, health claims, or other types of labeling statements on foods if they believe that consumers will be willing to pay more for products with specific attributes. We estimated semi-log hedonic price regressions for five breakfast bar and cereal product categories using Nielsen ScanTrack scanner data for 2004 and found that labeling statements for these foods are often associated with substantial increases in consumer willingness to pay. The largest effects were associated with "carbconscious" carbohydrate labeling (reflecting the time period of the data), followed by fat and sugar content labeling statements.

Purchase timing of households is usually modeled at the category level. Marketing efforts are however only available at the brand level. Hence, to describe category-level interpurchase times using marketing efforts one has to construct a category-level measure of marketing efforts from the marketing mix of individual brands. In this paper we discuss two standard approaches suggested in the literature to

Statistical offices use ,the matched ,models ,method ,to compile ,consumer ,price indices (CPIs) to measure,inflation. Price collectors record the prices of a ,sample ,of models ,or varieties of selected products existing in period t,and then continue to record the prices of these same matched models in subsequent,periods t+n. The matched,models,method,is designed,to control for quality changes,by ensuring that like is

The high resolution research tomograph (HRRT) is one of the most complex existing Positron Emission Tomographs: it is the only human size scanner capable of decoding the depth of the γ-ray interaction in the crystal, using a lutetium LSO/LYSO phoswitch detector arrangement. In this study we determined basic scanner hardware characteristics, such as scanner data acquisition stability, and their variability across eleven centres. In addition a subset of the NEMA NU-2001 standards measurements was performed. We found (i) significant variability in the DOI decoding results between centres, (ii) a trend toward an increasing number of detected true coincident events as a function of elapsed time from scanner calibration likely due to a shifting energy spectrum, (iii) a count-rate dependent layer identification, (iv) scatter fraction ranging from ∼ 42% to 54% where the variability was partly related to the shifting of the energy spectrum, (v) sensitivity ranging from ∼ 5.5% to 6.5% across centres, (vi) resolution of ∼ (2.5mm) 3 , fairly consistent across centres, (vii) image quality which is very comparable to other scanners.

The high resolution research tomograph (HRRT) is one of the most complex existing Positron Emission Tomographs: it is the only human size scanner capable of decoding the depth of the γ-ray interaction in the crystal, using a lutetium LSO/LYSO phoswitch detector arrangement. In this study we determined basic scanner hardware characteristics, such as scanner data acquisition stability, and their variability across eleven centres. In addition a subset of the NEMA NU-2001 standards measurements was performed. We found (i) significant variability in the DOI decoding results between centres, (ii) a trend toward an increasing number of detected true coincident events as a function of elapsed time from scanner calibration likely due to a shifting energy spectrum, (iii) a count-rate dependent layer identification, (iv) scatter fraction ranging from ∼ 42% to 54% where the variability was partly related to the shifting of the energy spectrum, (v) sensitivity ranging from ∼ 5.5% to 6.5% across centres, (vi) resolution of ∼ (2.5mm) 3 , fairly consistent across centres, (vii) image quality which is very comparable to other scanners.

During Leg 195 of the Ocean Drilling Program, Site 1202 was drilled in the subtropical northwestern Pacific Ocean beneath the Kuroshio ("Black Current") between northern Taiwan and the Ryukyu Island Arc on the northern flank of the Ilan Ridge at 1275 m water depth. The ridge separates the southwestern end of the Okinawa Trough from the basins of the Philippine

The data acquired from the hyperspectral airborne sensor DAIS-7915 over Izrael Valley in northern Israel was processed to yield quantitative soil properties maps of organic matter, soil eld moisture, soil saturated moisture, and soil salinity. The method adopted for this purpose was the Visible and Near Infrared Analysis (VNIRA) approach, which yields an empirical model for predicting the soil property in question from both wet chemistry and spectral information of a representative set of samples (calibration set). Based on spectral laboratory data that show a signi cant capability to predict the above soil properties and populations using the VNIRA strategy, the next step was to examine this feasibility under a hyperspectral remote sensing (HSR) domain. After atmospherically rectifying the DAIS-7915 data and omitting noisy bands, the VNIRA routine was performed to yield a prediction equation model for each property, using the re ectance image data. Applying this equation on a pixel-bypixel basis revealed images that described spatially and quantitatively the surface distribution of each property. The VNIRA results were validated successfully from a priori knowledge of the area characteristics and from data collected from several sampling points. Following these examinations, a procedure was developed in order to create a soil property map of the entire area, including soils under vegetated areas. This procedure employed a random selection of more than 80 points along nonvegetated areas from the quantitative soil property images and interpolation of the points to yield an isocontour map for each property. It is concluded that the VNIRA method is a promising strategy for quantitative soil surface mapping, furthermore, the method could even be improved if a better quality of HSR data were used.

We present a new technique for reconstructing a single shape and its non-rigid motion from 3D scanning data. Our algorithm takes a set of time-varying unstructured sample points that show partial views of a deforming object as input and reconstructs a single shape and a deformation field that fit the data. This representation yields dense correspondences for the whole sequence, as well as a completed 3D shape in every frame. In addition, the algorithm automatically removes spatial and temporal noise artifacts and outliers from the raw input data. Unlike previous methods, the algorithm does not require any shape template but computes a fitting shape automatically from the input data. Our reconstruction technique is based upon a novel topology aware adaptive sub-space deformation technique that allows handling long sequences with high resolution geometry efficiently. The algorithm accesses data in multiple sequential passes, so that long sequences can be streamed from hard disk, not b...

The continuous control of the conservation state of outdoor materials is a good practice for timely planning conservative interventions and therefore to preserve historical buildings. The monitoring of surfaces composition, in order to characterize compounds of neo-formation and deposition, by traditional diagnostic campaigns, although gives accurate results, is a long and expensive method, and often micro-destructive analyses are required. On the other hand, hyperspectral analysis in the visible and near infrared (VNIR) region is a very common technique for determining the characteristics and properties of soils, air, and water in consideration of its capability to give information in a rapid, simultaneous and not-destructive way. VNIR Hypespectral analysis, which discriminate materials on the basis of their different patterns of absorption at specific wavelengths, are in fact successfully used for identifying minerals and rocks (1), as well as for detecting soil properties includi...

Development of a crops and soils field research data base was initiated in 1972 at Purdue University's Laboratory for Applications of Remote Sensing and expanded in the fall of 1974 by the NASA Johnson Space Center as part of the Large Area Crop Inventory Experiment. The primary purpose for the data base is to provide fully annotated and calibrated multispectral sets of spectral, agronomic, and meteorological data for agricultural remote sensing research.

This paper uses scanner data from the bar-code readers of retailers to provide estimates of intercountry price parities at the level of the basic heading. The use of such data is appealing given its extensive coverage of transactions, information on weights, prices and characteristics of items at a highly detailed level. The study uses dummy variable hedonic and exact/superlative hedonic index number formulations applied to an inter-country context for both bilateral and multilateral comparisons. Unlike conventional methods, such methods are not confined to matched samples comparisons and thus make use of the entire sample. Their application extends to price survey data using checklists on characteristics. The application is to scanner data on about 1 million transactions for television sets over two months in three countries. It is, to the authors' knowledge, the first such use of scanner data and application of the above hedonic frameworks in this context.

While point of sale scanners have made the collection of high quality product movement data possible, the sheer volume of data has made market analysis and interpretation an overwhelming task. There is a growing demand for software tools that aid in interpreting marketing data. ...

Cloud properties were retrieved by applying the Clouds and Earth's Radiant Energy System (CERES) project Edition-2 algorithms to 3.5 years of Tropical Rainfall Measuring Mission Visible and Infrared Scanner data and 5.5 and 8 years of MODerate Resolution Imaging Spectroradiometer (MODIS) data from Aqua and Terra, respectively. The cloud products are consistent quantitatively from all three imagers, with the greatest discrepancies occurring over ice-covered surfaces. The retrieved cloud cover (~59%) is divided equally between liquid and ice clouds. Global mean cloud effective heights, optical depth, effective particle sizes, and water paths are 2.5 km, 9.9, 12.9 µm, and 80 gm-2 , respectively, for liquid clouds and 8.3 km, 12.7, 52.2 µ m, and 230 gm-2 for ice clouds. Cloud droplet effective radius is greater over ocean than land and has a pronounced seasonal cycle over southern oceans. Comparisons with independent measurements from surface sites, the Ice Cloud and Land Elevation Satellite, and the Aqua Advanced Microwave Sounder-EOS are used to evaluate the results. The mean CERES and MODIS Atmosphere Science Team cloud properties have many similarities but exhibit large discrepancies in certain parameters due to differences in unretrieved cloud pixels and algorithms. Problem areas in the CERES algorithms are identified and discussed.

In Austria about half of the entire area (46 %) is covered by forests. The majority of these are highly managed and controlled in growth. But besides timber production forest ecosystems play a multifunctional role including climate control, habitat provision and, especially in Austria, protection of settlements. The interrelationships among climatic, ecological, social and economic dimensions of forests require technologies for monitoring both the state and the development of forests. This comprises forest structure, species and age composition and, forest integrity in general. Assessing forest structure for example enables forest managers and natural risk engineers to evaluate whether a forest can fulfil its protective function or not. Traditional methods for assessing forest structure like field inventories and aerial photo interpretation are intrinsically limited in providing spatially continuous information over a large area. The Centre for Geoinformatics (Z_GIS) in collaboration with the National Park Bayerischer Wald, Germany and the Stand Montafon, Austria, has tested and applied advanced approaches of integrating multispectral optical data and airborne laser scanning (ALS) data for (1) forest stand delineation, (2) single tree detection and (3) forest structure analysis. As optical data we used RGBI line scanner data and CIR air-photos. ALS data were raw point data (10 pulses per sqm) and normalised crown models (nCM) at 0.5 m and 1 m resolution. (1) Automated stand delineation was done by (a) translating a key for manual mapping of forest development phases into a rule-based system via objectrelationship modelling (ORM); and (b) by performing multi-resolution segmentation and GIS analysis. (2) Strategies for single tree detection using raw ALS data included (a) GIS modelling based on a region-growth local maxima algorithm and (b) object-based image analysis using super class information class-specific rule sets. (3) Vertical forest structure has been assessed statistically by (a) applying basic statistics (like mean, standard deviation, and variation coefficient) on the raw data using a moving window approach; and (b) by applying landscape metrics (Shannon Evenness Index, SHEI, and division index, DIVI) for different strata extracted from the nCM.

We present a model of brand-switching in which a consumer's impression of each brand is based on her memory of past consumption of this brand, and is stochastically updated whenever the brand is consumed. In the ordinal version of the model, consumer's memory is an ordering of the available brands. The top brand is chosen and consumed, and may therefore

We discuss the basic theory of price indices. These form the basis for the Consumer Price Index in the United States. We note situations which can lead to non-robustness and volatility in several di erent price indices. An experiment to replace survey-based data with point of sales scanner data is being carried out. We visually explore the scanner data and conclude that certain aspects of scanner data can lead to non-robustness of commonly used price indices.

The calibration adjustment factors developed for the (wideband) shortwave scanning channels (SWSC) of the Nimbus-7 earth-radiation-budget instrument are checked by correlative comparison with the simultaneous data from channel 5 of the (narrowband) coastal-zone color scanner on the same platform. The problems of correlating narrowband and wideband data are discussed, and analytical and empirical relationships are developed on the basis of the satellite data and simulated data from the model-atmosphere dataset of Dave (1978). The previously established calibration adjustment factors are found to give relatively accurate results (to within 2 percent) for all of the five basic surface types investigated (vegetation, desert, cloud, water, and snow). Graphs and diagrams are provided.

Development of a crops and soils field research data base was initiated in 1972 at Purdue University's Laboratory for Applications of Remote Sensing and expanded in the fall of 1974 by the NASA Johnson Space Center as part of the Large Area Crop Inventory

The continuous control of the conservation state of outdoor materials is a good practice for timely planning conservative interventions and therefore to preserve historical buildings. The monitoring of surfaces composition, in order to characterize compounds of neo-formation and deposition, by traditional diagnostic campaigns, although gives accurate results, is a long and expensive method, and often micro-destructive analyses are required. On the other hand, hyperspectral analysis in the visible and near infrared (VNIR) region is a very common technique for determining the characteristics and properties of soils, air, and water in consideration of its capability to give information in a rapid, simultaneous and not-destructive way. VNIR Hypespectral analysis, which discriminate materials on the basis of their different patterns of absorption at specific wavelengths, are in fact successfully used for identifying minerals and rocks (1), as well as for detecting soil properties including moisture, organic content and salinity (2). Among the existing VNIR techniques (Laboratory Spectroscopy - LS, Portable Spectroscopy - PS and Imaging Spectroscopy - IS), PS and IS can play a crucial role in the characterization of components of exposed stone surfaces. In particular, the Imaging Spectroscopic (remote sensing), which uses sensors placed both on land or airborne, may contribute to the monitoring of large areas in consideration of its ability to produce large areal maps at relatively low costs. In this presentation the application of hyperspectral instruments (mainly PS and IS, not applied before in the field of monumental building diagnostic) to quantify the degradation of carbonate surfaces will be discussed. In particular, considering gypsum as the precursor symptom of damage, many factors which may affect the estimation of gypsum content on the surface will be taken into consideration. Two hyperspectral sensors will be considered: 1) A portable radiometer (ASD-FieldSpec FP Pro spectroradiometer), which continuously acquires punctual reflectance spectra in the range 350-2500 nm, both in natural light conditions and by a contact probe (fixed geometry of shot). This instrument is used on field for the identification of different materials, as well as for the definition of maps (e.g geological maps) if coupled with other hyperspectral instruments. 2) Hyperspectral sensor SIM-GA (Selex Galileo Multisensor Hyperspectral System), a system with spatial acquisition of data which may be used on an earth as well as on an airborne platform. SIM-GA consists of two electro-optical heads, which operate in the VNIR and SWIR regions, respectively, between 400-1000 nm and 1000-2500 nm (3). Although the spectral signature in the VNIR of many minerals is known, the co-presence of more minerals on a surface can affect the quantitative analysis of gypsum. Different minerals, such as gypsum, calcite, weddellite, whewellite, and other components (i.e. carbon particles in black crusts) are, in fact, commonly found on historical surfaces. In order to illustrate the complexity, but also the potentiality of hyperspectral sensors (portable or remote sensing) for the characterization of stone surfaces, a case study, the Facade of Santa Maria Novella in Florence - Italy, will be presented. References 1) R.N. Clark and G.A. Swayze, 1995, "Mapping minerals, amorphous materials, environmental materials, vegetation, water, ice, and snow, and other materials: The USGS Tricorder Algorithm", in "Summaries of the Fifth Annual JPL Airborne Earth Science Workshop", JPL Publication 95-1,1,39-40 2) E. Ben-Dor, K. Patin, A. Banin and A. Karnieli, 2002, "Mapping of several soil properties using DATS-7915 hyperspectral scanner data. A case study over clayely soils in Israel", International Journal of Remote Sensing, 23(6), 1043-1062 3) S. Vettori, M. Benvenuti, M. Camaiti, L. Chiarantini, P. Costagliola, S. Moretti, E. Pecchioni, 2008, "Assessment of the deterioration status of historical buildings by Hyperspectral Imaging techniques", in Proceedings of the "In situ Monitoring of Monumental Surfaces -SMS/08" Congress, Edifir-Edizioni Firenze 2008, 55-64

Choice-Based Conjoint (CBC) models are often used for pricing decisions, especially when scanner data models cannot be applied. To date, it is unclear how Choice-Based Conjoint (CBC) models perform in terms of forecasting real-world shop data. In this contribution, the performance of a latent class CBC model is measured not by means of an experimental hold-out sample but via aggregate scanner data. It is found that the CBC model does not accurately predict real-world market shares, thus leading to wrong pricing decisions. In order to improve its forecasting performance, a correction scheme based on scanner data is proposed. Our empirical analysis shows that the hybrid method improves the performance measures considerably.

Using AC Nielsen scanner data on U.S. household consumption of selected fresh vegetables from 1999 to 2003, this study provides an overview of the organic fresh vegetable market by investigating market shares and price premiums of selected organic fresh vegetables and estimating the interrelationship between consumer demand for organic and conventional fresh vegetables. The linear Almost Ideal Demand System was found to fit the data best among other differential demand models.

Commodity prices have been rising at unprecedented rates over the last two years. The primary objective of this paper is to assess if and how firms pass through upstream cost increases to final good prices. First, we investigate what happens to the shelf prices (the regular prices) of goods that contain significant amounts of a commodity whose price has changed. The objective is to document patterns of price rigidity depending on the share of the commodity in the final good that is sold to consumers. For example, given an abnormal commodity price change in wheat, what happens to the shelf regular price of bread, wheat cereals, and other goods that contain wheat? Commodity pass-through patterns for ready to eat cereal (smallest share of commodity in final product) and fresh chicken (largest share of commodity in final good) are investigated. Second, we also assess what happens to the net prices consumers pay (that is the regular price net of discounts offered). One possible way to pass through a cost increase is to reduce the frequency of promotional discounts, or offer smaller discounts to consumers. Upstream commodity input prices used in our investigation are wheat and corn futures prices, to account for upstream inputs, and flour and chicken feed producer price sub indices for downstream cost shocks.

We use scanner data of supermarket sales to investigate the effects of the EU School Fruit campaign, conducted in a sample of primary schools in the city of Rome during 2010 and 2011, on the consumption of unhealthy snacks. We allocate supermarkets to treatment and control groups depending on whether they are located or not near treated schools and estimate the causal effect of the program by comparing the changes in the sales of snacks in treated stores with the changes in control stores. We find evidence that the campaign reduced the consumption of unhealthy snacks bought in stores located in high income areas. No effect is found in poorer areas. Repeated treatment does not strengthen the effects of the program.

Consumers in developed countries are increasingly interested in the consumption of products incorporating ethical aspects, particularly fair trade products. They are usually distributed in a network of World Shops and more recently also introduced in supermarkets and shopping centres. The fair trade product with the highest share on the total is coffee. This study aims to ascertain the implicit price paid by Italian consumers for the fair trade content of coffee. The sample utilised is based on the purchase data of a representative sample of supermarket and shopping centre consumers observed from 1998 to 2002. Since scanner data are used, the analysis can allow for the numerous coffee attributes described by the labels: branded, organic, decaffeinated, fair trade, soluble, and so on. The empirical approach followed is the calculation of hedonic prices for the fair trade content and other attributes of coffee.

Simultaneous acquisition of surface chlorophyll-a concentrations for 39 samples from boats and Daedalus 1260 Multispectral Scanner data from a U-2 aircraft was conducted in the northern reaches of San Francisco Bay on 28 August 1980. These data were used to develop regression models for predicting surface chlorophyll-a concentrations over the study area for ebb-tide (8.40 a.m. P.D.T. (Pacific Daylight Time))

Simulated and real experimental data are used to investigate the use of (1) active computed tomography (ACT) to obtain images of attenuated gamma rays from a waste-canister interior; (2) passive computed tomography (PCT) to locate and determine the radioisotopic sources present; and (3) ACT data to correct PCT data so that accurate radioisotopic source activities can be determined. Active and passive computed tomography (A&PCT) techniques were used to analyze a small container of mock waste. Both simulated and experimental results reveal that ACT scans properly map the canister`s attenuating matrix and, coupled with PCT scans, can yield quantitative source activities.

Neuroimaging studies in bipolar disorder report gray matter volume (GMV) abnormalities in neural regions implicated in emotion regulation, including ventral/orbital medial prefrontal cortex (OMPFC) GMV decreases and, more inconsistently, amygdala GMV increases. We aimed to examine OMPFC and amygdala GMV in bipolar disorder, type 1 patients (BPI) versus healthy control participants (HC), and examine potential confounding effects of gender, clinical and illness history variables and psychotropic medication upon any group differences that were demonstrated in OMPFC and amygdala GMV. Images were acquired from 27 BPI (17 euthymic, 10 depressed) and 28 age-and gender-matched HC in a 3T Siemens scanner. Data were analyzed with SPM5 using voxel-based morphometry to first examine main effects of diagnostic group and gender upon whole brain (WB) GMV. Post hoc analyses were subsequently performed to examine the extent to which clinical and illness history variables and psychotropic medication contributed to GMV abnormalities in BPI in a priori and non-a priori regions demonstrated by the above VBM analyses. Here, SPPSS was used to examine the effects of these variables on magnitude of GMV in these a priori and nona priori regions in BPI versus HC. BPI showed reduced GMV in two regions established a priori: bilateral posteromedial rectal gyrus (PMRG), but no amygdala GMV abnormalities. BPI also showed reduced GMV in two non-a priori regions: left parahippocampal gyrus and left putamen. For left PMRG GMV, there was a significant group by gender by trait anxiety interaction. GMV was significantly reduced in male low trait anxiety BPI versus male low trait anxiety HC, and in high versus low trait anxiety male BPI. Our findings show in BPI significant effects of male gender and high trait anxiety on GMV reduction in left PMRG, part of the OMPFC medial prefrontal network implicated in visceromotor and emotion regulation.

Consumers in developed countries are increasingly interested in the consumption of food products incorporating ethical aspects, particularly fair trade products. These products are usually distributed in a network of World Shops and, more recently, in supermarkets and shopping centres. The fair trade product with the highest market share is coffee. This study aims to ascertain the implicit price paid by Italian consumers for the fair trade content of coffee and how this implicit price is influenced by the level of social capital of the territory where consumers live. The data utilised are scanner data, based on the purchase at supermarkets and shopping centres observed from 2005 to 2007, referred to a territorial unit that is the province. Since scanner data are used, the analysis can allow for the coffee attributes described by the labels: branded, organic, decaffeinated, fair trade, espresso, and so on. The approach followed is the application of an hedonic regression where the de...

Purchase timing of households is usually modeled at the category level. Marketing efforts are however only available at the brand level. Hence, to describe category-level interpurchase times using marketing efforts one has to construct a category-level measure of marketing efforts from the marketing mix of individual brands. In this paper we discuss two standard approaches suggested in the literature to solve this problem, that is, using individual choice shares as weights to average the marketing mix, and the inclusive value approach. Additionally, we propose three alternative novel solutions, which have less limitations than the two standard approaches. The new approaches use brand preferences following from a brand choice model to capture the relevance of the marketing mix of individual brands. One of these approaches integrates the purchase timing model with a brand preference model.

This paper uses over two years of weekly scanner data from two small US cities to characterize time and state dependence of grocers' pricing decisions. In these data, the probability of a nominal adjustment declines with the time since the last price change even after controlling for heterogeneity across store-product cells and replacing sale prices with regular prices. We also detect state dependence: The probability of a nominal adjustment is highest when a store's price substantially differs from the average of other stores' prices. However, extreme prices typically reflect the selling store's recent nominal adjustments rather than changes in other stores' prices.

This paper outlines the potential use of bar-code scanner data from retailers for the measurement of in¯ation. The source bene®ts from its extensive coverage in providing data on prices, quantities and values of transactions of each model of a good sold. Relative weights can thus be ascribed to price changes in both base and current months at a highly detailed level which allows us to estimate substitution bias. Methods of adjusting for quality changes can be considered. The dummy variable hedonic approach is compared with a superlative, exact hedonic approach and a matching technique akin to that used by statistical of®ces.

Much attention has been given to the estimation of hedonic regressions given their potential use as a means to adjust consumer and producer price indices for quality changes. However, there has been warranted criticism over the methods used, particularly relating to the econometric specification of the models. Much of the criticism has arisen from the inability of available data to match the requirements of a fully specified model. Using EPOS scanner data for UK television sets we provide reliable hedonic estimates which incorporate several developments. Such data are available for a wide range of product areas and this application illustrates how they might be used. We develop methodology to help surmount problems arising from omitted variables, the coexistence of new and old models, weighting of observations and quality changes common to all models. More specifically we pay particular attention to the neglected area of product markets where pricing is above marginal cost.

The present paper concentrates on the nature a nd structure of inter-store price competition. It focusses especially on price competition between different retailers within one trading area a nd within one product category. Six theoretically founded hypotheses postulate competitive relations between manufacturers’ UPCs and the retailers covering various possible competitive conditions such as competitive independencies or various degrees of

This paper aims to provide an answer to the question of out-of-stock events (OOS), their frequency, the sales losses they generate, and their causes. The authors provide two contributions. They describe a new sales-based measure of OOS computed on the basis of store-level scanner data and identify several of the main determinants of OOS. They also introduce a significant distinction

of "ProSmart" now %bk products. The airborne e x p h e n t a l SAR E-SAR of DLR contributes theh geocoded SAR imageiyof ~ ~ -~ ~ €n P h s e A of the project ABLSmartSPECTRAL a market surveyprotidd& main characteristics ofbatkkmid optical sensor s y s e t w~ As this paper reports about generatitlg bvel-3 SAR products only the miemwave The SAR satellite mission &all provide ~ two wavelengths, X (3 em-) and L (23 cm), higF3psWresolution, SAR polarimetry in L-Bm& and SAH interferometry for topographic mapping.

During the 1980s, there was a dramatic increase in the installation of systems which capture Point-of-Sale (POS) data by retailers. The increase of installations was greatest in the supermarket segment, after the adoption of an industry standard for bar coding (i.e. the Universal Product Code) by the consumer packaged goods manufacturers. The reported benefits from this adoption of standards has led to similar standards by vendors of other lines of consumer goods (e.g. apparel) carried by department stores and mass merchandisers. The initial impetus for retailers to install sophisticated POS systems was to decrease the time required to record the item purchases by customers, and to improve the accuracy of prices charged at checkout. Both manufacturers and retailers believed, however, that even greater benefits might be realized when the POS data were analysed, and applied to improve the effectiveness and efficiency of marketing activities logistics.

Prior to the general availability of POS data, marketing was usually considered to be an art. One reason for this view was that measures of market performance were available only at very aggregate levels, temporally and geographically. This made it difficult to assess the effect of a specific marketing events (e.g. price promotions), which might have occurred for a brief period of time (e.g. one week) in a particular retail chain. Consequently, successful marketing was attributed to the intuitive understanding of consumer tastes, and the creativity of media advertising. The availability of weekly POS data at the household, store, account and market level, when coupled with measures of causal variables (e.g. store displays), provides the opportunity to obtain precise measures of the effect of different marketing events. However, in order to take advantage of the availability of these data, firms must take a more scientific approach to marketing, and an appropriate commitment of resources.

The decision to commit the resources necessary to effectively use these data, however, has proven to be neither simple nor obvious for most companies. While the cost to retain POS data as an electronic byproduct of transactional systems is low, the resources required to store and analyse these data are significant. In addition, attributing improvements in bottom-line profitability to the direct application of these data has proven difficult.

The purpose of this chapter is to discuss the form and content of POS data available to marketers, how these data supplement and replace other forms of marketing data, and issues which have arisen in their effective managerial use. In the first two sections, we discuss the data as generated from transactions, and as applied in the two-stage channel structure which is common in consumer goods marketing. In the third section, a learning curve of expertise in the science of marketing is introduced. The following four sections review some leading-edge applications. The chapter concludes with an outlook on the future for POS data.