This study illustrates the use of ACNielsen Homescan Panel (HSD) in three separate demand analyses of dairy products: (1) the effect of using cross-sectional data in a New Empirical Industrial Organization (NEIO) study of ice cream firm mergers in San Antonio; (2) the estimation of hedonic price models for fluid milk by quart, halfgallon and gallon container sizes; (3) the estimation of a demand system including white milk, flavored milk, carbonated soft drinks, bottled water, and fruit juice by various container sizes. In the NEIO study a standard LA/AIDS demand system was used to estimate elasticities evaluating seven simulated mergers of ice cream manufactures in San Antonio in 1999. Unlike previously published NEIO work, it is the first to use crosssectional data to address the issue associated with inventory effects. Using the method developed by Capps, Church and Love, none of the simulated price effects associated with the mergers was statistically different from zero at the 5% confidence level. In 1995 Nerlove proposed a quantity-dependent hedonic model as a viable alternative to the conventional price-dependent hedonic model as a means to ascertain consumer willingness to pay for the characteristics of a given good. We revisited Nerlove’s work validating his model using transactional data indigenous to the HSD. Hedonic models, both price-dependent and quantity-dependent, were estimated for the characteristics of fat content, container type, and brand designation for the container sizes of gallon, half- gallon, and quart. A rigorous explanation of the interpretation between the estimates derived from the two hedonic models was discussed. Using the Almost Ideal Demand System (AIDS), a matrix of own-price, crossprice, and expenditure elasticities was estimated involving various container sizes of white milk, flavored milk, carbonated soft drinks, bottled water, and fruit juices, using a cross-section of the 1999 HSD. We described price imputations and the handling of censored observations to develop the respective elasticities. These elasticities provided information about intra-product relationships (same product but different sizes), intrasize relationships (different products same container size), and inter-product relationships (different products and different sizes). This container size issue is unique in the extant literature associated with non-alcoholic beverage industry.

Using household level scanner data for 2006, 2007, and 2008, this dissertation consists of four studies, which present household- and market-level analyses of food safety issues concerning the 2007 Peter Pan recall on the demand for peanut butter at the category level and at the brand level. Findings of the first study suggested that the recall had a statistically significant positive effect on the demand for peanut butter at the category level. At the brand level, spillover effects were evident in that the demand for Jif was positively affected, while the demand for Skippy was negatively affected. The second study examined structural change in the demand for peanut butter using demand system models corresponding to the pre-recall and the post-recall periods. Matrices of own-price, cross-price, and expenditure elasticities were calculated for both recall periods, and upon comparison, there were statistical differences in the corresponding estimated elasticities. In general, most price elasticities in the post-recall period were larger in absolute value than the comparable elasticities in the pre-recall period. The third study investigated the impact of household socio-economic characteristics associated with choices to purchase peanut butter across the pre- and the post-recall periods. Four choice scenarios were no buy-no buy, buy-no buy, no buy-buy, and buy-buy. Socio-economic characteristics considered included age, employment, education, race, ethnicity, presence of male and/or female household head, region, age and presence of children in the household, household size, and income. While the results varied by brand, region was the socio-demographic characteristic that was consistently significant among the choice scenarios for the respective peanut butter brands. Conditional on households purchasing peanut butter in both the pre- and the post-recall periods, the final analysis examined the influence of the same aforementioned socio-economic variables as well as the change in the own price on the change in the quantity purchased. The results varied across brands, but the principal drivers of the conditional change in the quantity purchased were the change in the own price and the age and presence of children in the household.

Laser scanners provide a three-dimensional sampled representation of the surfaces of objects. The spatial resolution of the data is much higher than that of conventional surveying methods. The data collected from different locations of a laser scanner must be transformed into a common coordinate system. If good a priori alignment is provided and the point clouds share a large overlapping region, existing registration methods, such as the Iterative Closest Point (ICP) or Chen and Medioni’s method, work well. In practical applications of laser scanners, partially overlapping and unorganised point clouds are provided without good initial alignment. In these cases, the existing registration methods are not appropriate since it becomes very difficult to find the correspondence of the point clouds. A registration method, the Geometric Primitive ICP with the RANSAC (GPICPR), using geometric primitives, neighbourhood search, the positional uncertainty of laser scanners, and an outlier removal procedure is proposed in this thesis. The change of geometric curvature and approximate normal vector of the surface formed by a point and its neighbourhood are used for selecting the possible correspondences of point clouds. In addition, an explicit expression of the position uncertainty of measurement by laser scanners is presented in this dissertation and this position uncertainty is utilised to estimate the precision and accuracy of the estimated relative transformation parameters between point clouds. The GP-ICPR was tested with both simulated data and datasets from close range and terrestrial laser scanners in terms of its precision, accuracy, and convergence region. It was shown that the GP-ICPR improved the precision of the estimated relative transformation parameters as much as a factor of 5. / In addition, the rotational convergence region of the GP-ICPR on the order of 10°, which is much larger than the ICP or its variants, provides a window of opportunity to utilise this automated registration method in practical applications such as terrestrial surveying and deformation monitoring.

Doctor of Philosophy / Department of Agricultural Economics / Hikaru Hanawa Peterson / Consumers’ food demand has been found to be affected not only by prices and income, but also by their increasing concern about factors like health benefits, animal welfare, and environmental impacts. Thus, many food producers have differentiated and advertised their products using relevant attributes. The increasing demand and supply of differentiated food products have raised questions regarding consumer preferences and producer strategies. This dissertation consists of three essays and empirically examines the egg market to shed light on related issues. The first question that this study aims to answer is whether consumers are willing to pay a premium for livestock and dairy products associated with improved animal welfare. Consumers’ attitude towards such products not only affect manufacturers’ production decisions, but also influence policy makers and current legislations. Using a national online survey with choice experiments, the first essay found that consumers in the study sample valued eggs produced under animal-friendly environment, suggesting incentives for producers to adopt animal welfare friendly practices. In an actual shopping trip, consumers usually need to choose from products with multiple attributes and labels. Studying how consumers with heterogeneous preferences process these information simultaneously and make decisions is important for producers to target interested consumer segments and implement more effective labeling strategies. In the second essay, a different national online survey was administered. The analysis using a latent class model categorized the sample respondents into four classes, and their preferences toward attributes and various label combinations differed across classes. Scanner data, which record actually purchased choices, are an important source of information to study consumer preferences. Diverging from the traditional demand approaches that are limited in studying differentiated product markets using scanner data, this study used a random coefficient logit model to overcome potential limitations and examine the demand relationship as well as price competition in the differentiated egg market. The third essay found that conventional and private labeled eggs yielded higher margins due to less elastic demand and cautioned producers of specialty eggs, which are usually sold at high prices despite their much more elastic demand.

Master of Science / Department of Agricultural Economics / Ted C. Schroeder / It is clear that consumers rely on certain experience and credence attributes when purchasing beef products from the retail meat case. It is essential for all beef industry sectors to recognize the complexity of consumers buying behavior. The objective of this research is to determine if there are incentives to brand beef products and to determine what types of brands entertain price premiums as well as what levels these premiums exists. Retail scanner data, collected from 2004 through March 2009, was used for the evaluation of branded beef and also to determine what other product attributes benefit with a premium to six specific cuts of beef. Hedonic models were estimated using Ordinary Least Squares regressions to determine which variables affected the overall price per pound of each of the six cuts of beef chosen to analyze. Results indicate that there is an incentive to brand beef products at the retail level. Local, regional, national, and store brands all garnered premiums across the six models for the beef cuts, steak, roast, ground, strip, cube, and ribs in relation to products with no brand. Other variables that garnered premiums across all models include organic, Prime quality grade, and Kosher and Kosher-Glatt religious labels. Steak exhibited the highest mean price per pound followed by cube, roast, strip, ribs and ground. In all of the models estimated explaining price variation, there were few coefficients that were statistically insignificant. Additional modeling was done to determine if outlier observations were influencing the regression results. The sensitivity analyses resulted in small changes in parameter estimates indicating the identified influential observations did not have undue impact on the parameter estimates.

Vermont is the first and only state in the US to establish mandatory labels for food containing genetically modified organisms (GMOs). This thesis investigates the impact of the mandatory labeling law as it relates to changes in prices, quantities sold, and opinions of GMOs. First, grocery store scanner data from Vermont and Oregon are compared using triple difference (difference-in-difference-in-difference) models. Next, Vermont, Oregon, and Colorado survey response data are compared using difference-in-difference models. The findings reveal that there is a general price premium for non-GMO goods of $0.05/oz across all states and times, that mandatory labeling laws do not result in a short-term change in quantities sold or prices of GMO products, and that both mandatory labeling laws and failed mandatory labeling referendums cause an increase in support for GMOs in the food supply. The implications of this research are that mandatory GMO labels did not impact short-term prices or sales and increased the level of support for GMOs.

Millions of dollars are spent each year on sales promotion in grocery retailing. Despite this, no one really knows wheter promotions for individual items have positive, neutral, or negative effects on the store’s total profits. In this dissertation, an attempt is made to build a framework model that can be used to predict and evaluate how specific promotions affect item-level, category-level, and store-level profits. One major contribution is that the proposed model specifically incorporates store-traffic and cannibalization effects. The book consists of four parts: the first part is a review of the literature on sales promotion. The second part describes the development of a model for measuring the profit of retailer promotions. The third part shows the impact of sales promotion on profits for a number of hypothetical products. The fourth part measures the profit impact of sales promotions for 15 items in three product categories. The data used in this study were collected in a Swedish supermarket in cooperation with ICA. / Diss. Stockholm : Handelshögskolan, 1995

Choice-Based Conjoint (CBC) models are often used for pricing decisions, especially when scanner data models cannot be applied. Up to date, it is unclear how Choice-Based Conjoint (CBC) models perform in terms of forecasting real-world shop data. In this contribution, we measure the performance of a Latent Class CBC model not by means of an experimental hold-out sample but via aggregate scanner data. We find 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, we propose a correction scheme based on scanner data. Our empirical analysis shows that the hybrid method improves the performance measures considerably. (author's abstract) / Series: Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science"

What characterises the grocery store — customer relation? Can grocery stores expect to have an active role in households’ management of everyday life? Can households, on the other hand demand active participation and help from the stores? By which methods can we learn more both about food-related consumer behaviour and about the relation between stores and consumers? Based on two empirical studies of consumer behaviour, this books deals with these issues. In the first part of the book an empirical study using 165 weeks of POS scanner data for fourteen product categories is presented. These data were used to analyse effects of different promotional activities, and the results indicated that in-store activities, particularly in the form of in-store display, were important. The results from the first study brought the question of store — customer relation into focus, why this relation was studied next. The second part of the book consists of this exploratory, empirical study applying participant interviewing. In this case it meant talking to grocery shoppers while observing them. Some ten households with small children were accompanied to the grocery store, providing a context based consumer perspective. Different aspects of food and purchasing, such as interest in food and the social role of the meal, were treated. Tentatively, the dimensions planning and involvement are suggested as dimensions by which to separate households or shopping trips from each other. If validated, these dimensions might be useful as instruments for retailers interested in adapting to their customers different needs and purchasing behaviours. The concluding part discusses the two empirical studies, both in terms of method and in terms of contribution to knowledge on consumer behaviour. One important issue is here the value, for a single researcher, of combining two studies with such different methods. / Diss. Stockholm : Handelshögsk.

This dissertation focuses on topics in areas of agricultural and food policy, international trade, agricultural markets and marketing. The dissertation is structured as three papers. The first paper, Chapter 1, evaluates the impact of agricultural trade policies. Imported shrimp, which comprises nearly ninety percent of all United States shrimp consumption, have become the subject of antidumping and countervailing duty investigations in the past decade. I estimate the import demand for shrimp in the United States from 1999-2014, using the Barten’s synthetic model. I test the hypothesis of possible structural breaks in the import demand introduced by various trade policies: antidumping/countervailing duty investigations and impositions, and import refusals due to safety and environmental issues. Results show that these import-restricting policies have significant effects on the import shrimp demand, indicating that the omission of them would lead to biased estimates. Chapter 2, the second paper, examines how the burden of state cigarette tax is divided between producers/retailers and consumers, by using the Nielsen store-level scanner data on cigarette prices from convenience stores over the period 2011–2012. Cigarette taxes were found more than fully passed through to retail prices on average, suggesting consumers pay excess burden and market power exists in the cigarette industry. Utilizing information on the attributes of cigarette products, we demonstrated that tax incidence varied by brand and package size: pass-through rates for premium brands and carton-packaged cigarettes are higher than those for discount brands and cigarettes in packs, respectively, indicating possibilities of different demand elasticities across product tiers. Chapter 3, the third paper, focuses on identifying the demographic characteristics of households buying organic coffee, by examining the factors that influence the probability that a consumer will buy organic coffee, and which factors affect the amount organic coffee purchased. Using nationally representative household level data from 55,470 households over the period of 2011 to 2013 (Nielsen Homescan), and a censored demand model, we find that economic and demographic factors play a crucial role in the household choice of purchasing organic coffee. Furthermore, households are less sensitive to own-price changes in the case of organic coffee versus conventional coffee.