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The objective of this research is to examine, validate, and recommend techniques for handling the problem of missingness in observational data. We use a rich observational data set, the Nielsen HomeScan data set, which allows us to effectively combine elements from simulated data sets: large numbers of observations, large number of data sets and variables, allowing elements of “design” that typically come with simulated data, and its observational nature. We created random 20% and 50% uniform missingness in our data sets and employed several widely used methods of single imputation, such as mean, regression, and stochastic regression imputations, and multiple imputation methods to fill in the data gaps. We compared these methods by measuring the error of predicting the missing values and the parameter estimates from the subsequent regression analysis using the imputed values. We also compared coverage or the percentages of intervals that covered the true parameter in both cases. Based on our results, the method of single regression or conditional mean imputation provided the best predictions of the missing price values with 28.34 and 28.59 mean absolute percent errors in 20% and 50% missingness settings, respectively. The imputation from conditional distribution method had the best rate of coverage. The parameter estimates based on data sets imputed by conditional mean method were consistently unbiased and had the smallest standard deviations. The multiple imputation methods had the best coverage of both the parameter estimates and predictions of the dependent variable.

This paper empirically investigates the demand for pastured eggs in the United States and evaluates the welfare consequences of Japan's egg import tariff reductions for the US consumers.

Using household-level Nielsen Homescan panel data, a fixed-effects Heckman two-stage sample selection model is estimated.

The estimation results ascertain the importance of a set of household socioeconomic characteristics, which are found to influence both the purchase probabilities and the consumption amounts associated with pastured eggs. In addition, demand for pastured eggs is estimated to be inelastic, and pastured eggs are found to be a normal good, more specifically a luxury.

The dataset used in this study reflect purchases only for at-home consumption, lacking information on away-from-home purchases.

Building upon previous research, this study makes the following distinct contributions to the current literature. To the best of our knowledge, it constitutes the first study to empirically examine the demand for pastured eggs, using household-level panel data and an estimation model that not only allows for left-censoring but also controls for regional and time fixed effects. Second, the present study reflects a unique effort in analyzing the adverse welfare consequences of the increased egg prices in the United States brought by a reduction of Japanese import tariffs on US-supplied eggs, focusing specifically on pastured eggs.

The purpose of this paper is to compare prices for fresh tomatoes, potatoes, peppers, and apples at direct-to-consumer sales outlets (e.g. farmers markets, roadside stands, on-farm stores) in the USA to grocery stores and supercenters, while controlling for other attributes.

The author estimates a hedonic regression model to determine price differences at direct sales outlets, grocery stores, and supercenters in various regions and seasons of the year. The analysis is conducted using 2006 Nielsen Homescan data. Other product and market attributes are also considered, along with characteristics of the household sample.

Prices at direct sales outlets are lower than grocery store prices throughout the year and across the USA. Prices at direct sales outlets for some product/location/season combinations were higher than or comparable to supercenter prices.

Future research is needed to examine how price differences may vary across the various types of direct marketing outlets.

Few studies have examined price differences between direct sales outlets and conventional retail stores. No studies have used nationally representative data to analyze these price differences across produce type, season, and geographic areas.

The purpose of this paper is to investigate the factors affecting consumer demand for and the effects on tax on sparkling and non-sparkling bottled water in the USA.

Using nationally representative data from 62,092 households and tobit econometric procedure, conditional and unconditional factors affecting the demand for sparkling and non-sparkling bottled water were estimated.

The own-price elasticity of demand for sparkling and non-sparkling bottled water is −0.664 and −0.229, respectively. Coffee, fruit drinks, whole milk and tea are substitutes for non-sparking bottled water. Non-sparking bottled water, coffee, fruit drinks and whole milk are substitutes for sparking bottled water. Household income, race, region and presence of children significantly affect the demand for bottled water. A 10 percent increase in price due to a tax on bottled water decreased plastic use by 50 grams per household per year. This is equivalent to saving 9.5m pounds of plastic annually.

Data used in this analysis only captured at-home consumption of bottled water by US households. While tax on bottled water may reduce the consumption of bottled water, it may increase the consumption of competitive beverages such as carbonated soft drinks or fruit drinks. Although the use of plastic with regards to water bottles may go down as a result of the tax, the plastic consumption could go up with regards to consumers’ increased purchase of other beverages. This might contribute net increase plastic bottle consumption, undermining the effects of a bottled water tax.

To the best of the authors’ knowledge, this study is the first to look at demand and tax aspects with regards to disaggregated bottled water products.

In the age of “big data,” one of the most important capabilities that differentiates the winners from the losers in the intensely competitive grocery market is how successfully a firm can harness its vast amounts of shopper data to become more shopper-centric. Grocery retailers struggle with how to manage the tremendous amount of data available to them and best leverage their frequent shopper data to derive insights. These data also present an opportunity for academic research on decision-making and evaluation of strategic initiatives. This chapter discusses three case studies that illustrate the various capabilities of frequent shopper data in generating shopper insights. Specifically, using frequent shopper data for millions of shoppers, the three case studies demonstrate how frequent shopper data can be used as an important information asset for understanding differences and similarities among different shopper groups (Case Study 1), as a means to assess the effectiveness of store redesigns/environment changes (Case Study 2), and as a key tool for evaluating program success (Case Study 3). The chapter concludes with a discussion of how successful collaboration between practitioners and academics can be a boon to both business success and academic research.

The purpose of this paper is to identify and quantify the factors determining the prices of organic and conventional cheese. For a market with a high degree of product differentiation, i.e. the German cheese market, price premiums of various cheese attributes are examined. Thereby, special attention is paid to country of origin (CO) effects, geographical indications (GIs) and organic claims.

The analysis is based on homescan panel data of 13,000 representative German households provided by the GfK consumer research association. The data set combines actual purchase and demographic data for a five-year sample period from 2004 to 2008. Applying the hedonic technique, the cheese price is modelled as a function of a wide range of consumer, store and product characteristics. Effects are analysed in detail by distinguishing between supply- and demand-side effects and by estimating price regressions not only for the whole sample but also for different shop types.

The estimated organic price premiums range between 18 per cent in discount shops and 26 per cent in hypermarkets. The impacts of the CO and GIs are considerably smaller in magnitude and limited to special shopping venues like super- and hypermarkets.

The German cheese market is currently evolving from a staple product market to a highly differentiated market where increasing attention is paid to quality indicators such as organic claims or GIs. The data are remarkable, both in sample size and information content. Furthermore, the estimation of shop type-specific price premiums offers new and detailed insights in consumer valuation and producer costs of a wide range of cheese attributes.

This paper aims to show the effect of brand equity, marketing investment and product differentiation on price in small and medium enterprises (SMEs), multinational companies (MNCs) and retailers (private labels). Academics have been researching brand equity, return on investment and effects of product differentiation for many years, but there has been little work that has taken a holistic view.

The author studied an aggregate data set for 735 fast-moving consumer goods (FMCG) brands, taken from Nielsen (10,282 households). Regression analysis was used in the first step, a cluster analysis in the second step of modeling procedure.

The study suggests that brand equity, marketing investment and product differentiation are closely associated with price. Using a cluster analysis, the authors found that the premium price is significantly associated with product differentiation based on innovation and company type.

The managerial implications of the models estimated by regression analysis are discussed as well as the results of the cluster analysis and possible research enhancements.

The role of the value in brand performance output has not been investigated in the financial context, only in consumer or marketing mix context. Little is known about how price strategy depends on brand equity, product innovation activities or marketing investments intended to improve brand performance, neither how this strategy improves brand performance among different players in the market (retailers, SMEs and MNCs).

This research investigates the effect of imposing a tax on sugar-sweetened beverages (SSBs) on the likelihood of purchasing SSBs. We design and test an experimental framework that examines this and the effects of providing an explanation about the presence of an SSB tax and information about the negative health effects of consuming SSBs. Consistent with Elbel, Taksler, Mijanovich, Abrams, and Dixon (2013) and Taylor, Kaplan, Villas-Boas, and Jung (2019), we find that imposing a tax, in addition to increasing the conspicuousness of the tax by explaining the presence of a tax (and in some cases, the negative health effects) reduces the likelihood of purchasing an SSB anywhere from 8.39% to 18.15%. We contribute to the public health and tax policy literature by testing consumer choice in a controlled experimental setting and considering the effect of individual differences on the choice to purchase SSBs. Imposing a tax on SSBs may be an effective tool for decreasing SSB consumption that is made more effective when the tax is conspicuous.

The author aims to present a model of the brand value drivers, measured by brand equity. The goal of this research is to identify the drivers, and determine how they influence brand equity performance in the researched industry, in order to develop a more effective brand strategy.

The author studied an aggregate dataset for 739 food brands. Six predictors were controlled for (i.e. marketing investments, price, revenue, perceived quality [organic and functional] and brand ownership), while the impact of the brand equity drivers on brand value was estimated. The model was formulated and estimated using a robust OLS procedure. Several data sources have were in this study, such as market-based data from ACNielsen, as well as information and variable constructs using data from the Bureau Van Dijk Electronic Publishing AIDA financial statements database.

Results suggest that marketing investment, price, revenue, brand ownership and perceived quality are highly associated with brand equity, and consequently with a higher brand value in the food industry.

This study has only studied one industry (food), one industry segment (enriched-food) and one country (Italy).

The majority of marketing studies apply a single research approach and measures. This is the first study of brand equity that combines consumer, financial and marketing approaches. The model contributes to theory and practice in terms of suggesting which business drivers create brand value and what type of brand strategy a firm can apply in order to create brand value.

The purpose of this paper is to address how marketing assets and resources of the firm perform under different product (brand) innovation conditions using the dynamic marketing capabilities (DMC) research perspective. The study contributes to the DMC research stream showing the effects and performance of heterogeneous firm drivers and resources. Academic research to date has paid a little attention to the interrelationship between market share as a performance metric, dynamic capabilities and product (brand) innovation. The current study bridges this knowledge gap by empirically validating the effects of DMC on market share performance output using panel data for 753 retail food brands.

The model was initially fitted with the β regression analysis and cluster analysis in the second step of the estimation procedure. The results of simulation by Monte Carlo experimentation are discussed.

The findings show that firms leverage their marketing capabilities unequally in the multi-brand portfolios, which leads to an unequal intra-firm distribution of assets and resources. The research contributes to the understanding of the brand competitive dynamics and appropriate deployment of assets and resources for improved firm performance.

These findings are useful for both academics and practitioners because they address new and future research. In doing so, the authors advance the firm performance and branding literature with extension in the DMC literature.