Knowledge that Transforms

Critics have long faulted the wide-spread practice of trade promotions as wasteful. It has been estimated that this practice adds up to $100 billion worth of inventory to the distribution system. Yet, the practice continues. In this paper, we propose a price discrimination model of trade promotions. We show that in a distribution channel characterized by a dominant retailer, a manufacturer has incentives to price discriminate between the dominant retailer and smaller independents. While offering all retailers the same pricing policy, price discrimination can be implemented through trade promotions because they induce different inventory-ordering behaviors on the part of retailers. Differences in inventory holding costs have been shown to be an important determinant of consumer promotions. Our analysis suggests that differences in holding costs are also potentially an important driver for the use of trade promotions. The implications from our model explain a number of anecdotal and/or empirically observed puzzles about how trade promotions are practiced. For example, our analysis explains why chain stores welcome trade promotions but independents do not. Our analysis outlines implications for managing trade promotions.

In this paper, we propose and operationalize a new method for optimizing shelf arrangements. We show that there are important dependencies between the layout of the shelf and stock-keeping unit (SKU) sales and marketing effectiveness. The importance of these dependencies is further shown by the substantive profit gains we obtain with our proposed shelf optimization approach. The basis of our model is a standard sales equation that explains sales using item-specific marketing effect parameters and intercepts. In a Hierarchical Bayes (HB) fashion, we augment this model with a second layer that relates the effect parameters to shelf and SKU descriptors. We also take into account potential endogeneity of facings. After estimating the parameters of the two-level model using Bayesian methodology, we carefully investigate the dependencies of SKU sales and SKU marketing effectiveness on the shelf layout. Next, we search for the shelf arrangement that maximizes the expected total profit using simulated annealing (SA). We appear to be able to increase profits for all the stores analyzed, and our approach appears to outperform well-known rules of thumb.

We investigate the sensitivity of cross-brand pass-through estimates to two types of pooling: across stores, and across regular price and promotional price weeks. Using the category data from Besanko, Dubé, and Gupta (2005), hereafter BDG, we find consistent support across all 11 categories for the predictive power of the wholesale prices of substitute products for retail shelf prices. A Bayesian procedure is used to address the small sample issues that arise in the absence of pooling. Even though the unpooled results render our inferences for specific cross-brand pass-through magnitudes reported in BDG as imprecise, consistent with McAlister (2007), we do find significant empirical support for cross-brand pass-through. We next assess the sensitivity of cross-brand pass-through estimates to pooling. This requires us to construct a much longer time series of 224 weeks for the refrigerated orange juice category, in contrast with the 52-week samples used in BDG and McAlister (2007). We find strong empirical support for the predictive power of wholesale prices of substitute products for retail shelf prices. In addition, we find evidence of nonzero own- and cross-brand pass-through elasticities for which our inferences are much more precise. These findings are robust to the separation of regular and promotional price weeks. However, the magnitudes of own-brand and cross-brand pass-through are quite different during promotional and regular price weeks. Our results clearly show that with longer data series and more robust models that can handle small sample sizes, there is evidence of cross-brand pass-through, substantiating the findings in BDG. Finally, we comment on why our results are entirely consistent with both the theoretical and empirical literatures on category pricing and retailer behavior.

This paper seeks to quantify the long-term financial impact of negative word of mouth (NWOM), an issue that has long challenged extant research. We do so with real-world data on firm security prices. The developed time-series models innovatively uncover (1) short- and long-term effects of NWOM on cash flows, stock returns, and stock volatilities, and (2) NWOM's “wear-in” effects (i.e., it takes a number of months before the stock price impact of NWOM reaches the peak point) and “wear-out” effects (i.e., it takes several months after the peak before the stock price impact of NWOM dies out completely). In addition, the results related to endogeneity and feedback effects from the stock market are also interesting, supporting the idea that historical underperformance in stock prices may breed more harmful future buzz in a “vicious” cycle of NWOM. After controlling for competition, NWOM's long-term financial harm becomes more destructive in magnitude, kicks in more quickly, and haunts investors longer. Overall, these findings offer some unique implications for buzz management, time-series models quantifying the financial impact of word of mouth, and the marketing-finance interface.

We investigate biases in product valuation and usage decisions that arise when consumers consider a new generation of a product that offers an expanded set of capabilities of uncertain value. Two experiments using a novel computer game show evidence of a valuation-usage disparity: Participants display a high willingness to pay for a new version of the game that offers a new set of controls, but fail to fully exercise the option to use these controls after purchase. This discrepancy is attributed to a fundamental difference in how new capabilities are valued at the time of purchase versus use. Consumer usage decisions appear to be driven by such myopic concerns as a desire to avoid short-term learning costs, whereas purchase decisions often fail to take into account the factors that drive usage, and are further inflated by global optimism in the future usefulness of new capabilities. We show that this lack of foresight can be explained by an intertemporal judgment model in which consumers attempt to value the option to use new capabilities as would be prescribed by economic theory, but are prone to hyperbolic discounting in their temporal valuation of present versus future costs and benefits.

We investigate price competition between firms in markets characterized by consumer variety seeking. While previous research has addressed the effect of consumer inertia on prices, there exists no research on the effects of variety seeking on price competition. Our study fills this gap in the literature. Using a two-period duopoly framework as in Klemperer's analysis of inertial markets, we show that the noncooperative pricing equilibrium in a market with consumer variety seeking may be the same as the collusive outcome in an otherwise identical market without variety seeking. Specifically, our variety-seeking model implies tacit collusion between firms in both periods, unlike the inertia model of Klemperer that implies tacit collusion between firms only in the second period but implies fierce price competition in the first period. When consumers are assumed to have rational expectations about future prices, the implied first-period prices increase further, which is consistent with what Klemperer finds in an inertial market. To summarize, while our variety-seeking analyses support two key results (pertaining to second-period prices and rational expectations) previously derived for inertial markets by Klemperer, they depart from one key result (pertaining to first-period prices).