Balancing Profitability and Customer Welfare in a Supermarket Chain

We investigate the impact of price discrimination by a large Chicago supermarket chain. First we measure the impact of the chain's current zone-pricing policy on shelf prices, variable profits and consumer welfare across its stores. Using the chain's database to simulate a finer store-specific micro-pricing policy, we study the implications of this policy on profits and welfare. We show how a store-pricing policy that is constrained to offer consumers at least as much surplus as a uniform chain wide pricing policy still enables the retailer to generate substantial incremental profits.To ensure our pricing problem exhibits a well-defined optimum, we use the parsimonious, mixed-logit demand function that allows for flexible substitution patterns across brands and also retains a link to consumer theory. We discuss the issue of price endogeneity when estimating the demand parameters with weekly store-level data. Standard instrumental variables techniques used to account for such endogeneity also seem to increase the magnitudes of own-price elasticities thereby offsetting the problem encountered by previous researchers of predicted prices from a demand model exceeding those in the actual data.     

Investigating the effects of a line extension or new brand introduction on market structure

Market structure has been characterized by the locations of brands in the perceptual space of households (perceptual map) and the importance weights associated with the attributes of this map. It is hypothesized that a line extension or a new brand introduced into this market could potentially affect the brand locations or the importance weights. We show how a simple extension of a recent approach to market structure analysis enables us to empirically identify which, if any, of these two aspects of market structure is affected by the line extension or new brand. An empirical application to the detergent product market is provided.     

Modeling and Forecasting the Sales of Technology Products

Managers in technology product markets require sales response models that provide substantive insights into the effects of marketing activities as well as reliable sales forecasts. Such markets are characterized by frequent introductions and withdrawals of multiple models by different companies. Thus, the data available on the performance of any individual model is scarce. A second characteristic is that the effects of product attributes and marketing activities could change over time as different types of consumers participate in the market at different points in time. Given sparse data, it becomes critical to specify a model that allows pooling of information across brand-models while at the same time providing brand-model specific parameters. We accomplish this via a hierarchical Bayesian model specification. Further, to capture the effects of changing consumer preferences over time, we specify a time varying parameter model. Our modeling framework therefore, integrates a hierarchical Bayesian model within a time varying parameter framework to develop a dynamic hierarchical Bayesian model. We employ data on digital cameras in the U.S. market to estimate the parameters of our proposed model. We use thirty-three months of national level data on the digital camera market with the data series beginning very close to the inception of this product category. We find that while there is little variation in reliance of benefits by early adopters, the second wave of adopters focus on Ease of Use followed by later adopters who rely on Storage and Image Quality. Looking at the elasticities of demand with respect to the various benefits, we find that at around the halfway point of our data series, the industry as a whole would have been better off investing in increasing image quality rather than storage if costs associated with the two are equal. However, at the end of the time horizon both benefits appear to have about equal impact. Further, the relative benefits of improving these attributes vary across brands and points in time. We then generate single period and multiple period ahead sales forecasts. We make different assumptions about information availability and find that the average (across brand-models and time) MAPE ranges from 7.5 to 14.5% for the model. We provide extensive comparisons of our model with 4 potential alternatives and find that our model outperforms these alternatives on the nature of substantive insights obtained as well as in forecasting out-of-sample especially when there is a very short time window of data.     

Representing Heterogeneity in Consumer Response Models 1996 Choice Conference Participants

We define sources of heterogeneity in consumer utility functions relatedto individual differences in response tendencies, drivers of utility, formof the consumer utility function, perceptions of attributes, statedependencies, and stochasticity. A variety of alternative modelingapproaches are reviewed that accommodate subsets of these various sourcesincluding clusterwise regression, latent structure models, compounddistributions, random coefficients models, etc. We conclude by defining anumber of promising research areas in this field.     

Structural Applications of the Discrete Choice Model

A growing body of empirical literature uses structurally-derived economic models to study the nature of competition and to measure explicitly the economic impact of strategic policies. While several approaches have been proposed, the discrete choice demand system has experienced wide usage. The heterogeneous, or mixed, logit in particular has been widely applied due to its parsimonious structure and its ability to capture flexibly substitution patterns for a large number of differentiated products.We outline the derivation of the heterogeneous logit demand system. We then present a number of applications of such models to various data sources. Finally, we conclude with a discussion of directions for future research in this area.     

Store Brands: Who Buys Them and What Happens to Retail Prices When They Are Introduced?

Review of Industrial Organization - In this paper we study store brand demand behavior by examining a panel ofhousehold level and store-level data in five stores located in a competing marketarea....     

Comments on “Counterfactual Inference for Consumer Choice Across Many Product Categories”

Quantitative Marketing and Economics -     

Retailer Pricing and Competitive Effects

Until recently, retailers have taken an either/or approach to competition: either reacting fiercely to competitive price changes or ignoring them altogether. Today, however, firms make a concerted effort to determine and quantify competitive effects. In this paper, we focus on how pricing and competitive effects interact as a general phenomenon, particularly as it applies to retailing. We attempt to construct a general framework that enhances our understanding of the emerging research issues in the area of pricing and competitive effects, and we examine their implications for practice. The areas that show high promise/opportunity are in the online setting for all types of goods—fashion, perishable and packaged staples, and durables—particularly with respect to pricing for profitability and understanding the impact of competition. Other opportunities include understanding the pricing and competitive effects in the perishable goods category sold in specialty, discount, and convenience stores.     

Equilibrium pricing and advertising strategies for nondurable experience products in a dynamic duopoly

The quality of many consumer nondurable goods or services is sufficiently complex or obscure that consumers cannot completely verify the true quality in a single usage. For such ‘experience’ products or services, the accumulated consumer consumption experience of a brand is an important determinant of its sales or market share. The market share of a brand is in turn directly influenced by its own and the competitive price and advertising strategies, given the different levels of quality (among other factors). In this paper, we investigate the impact of the aggregate consumption experience on the firm's dynamic pricing and advertising strategies by developing a formal game-theoretic model of a dynamic duopoly. The model of competition does not yield explicit closed-form expressions for the dynamic price and advertising paths of the two firms. Hence, we simulate the equilibrium paths using a discrete-time algorithm. Our simulation results provide interesting insights into the dynamic equilibrium price and advertising paths, under a variety of realistic competitive scenarios.