Category: Price

with Raoul Kubler, Thomas Fandrich and Gokhan Yildirim, Journal of Marketing, 82(5), 2018, 20-44.

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Many companies compete globally in a world in which user ratings and price are important drivers of performance but whose importance may differ by country. This study builds on the cultural, economic, and structural differences across countries to examine how app popularity reacts to price and ratings, controlling for product characteristics. Estimated across 60 countries, a dynamic panel model with product-specific effects reveals that price sensitivity is higher in countries with higher masculinity and uncertainty avoidance. Ratings valence sensitivity is higher in countries with higher individualism and uncertainty avoidance, while ratings volume sensitivity is higher in countries with higher power distance and uncertainty avoidance and those that are richer and have more income equality. For managers, the authors visualize country groups and calculate how much price should decrease to compensate for a negative review or lack of reviews. For researchers, they highlight the moderators of the volume and valence effects of online ratings, which are becoming ubiquitous in this connected world.

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with Cenk  Kocas, and Jonathan D. Bohlmann. ” Journal of Interactive Marketing 41, 2018, 28-43.

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Among the many items online retailers sell, some stand out as best sellers and are often sold at considerable discounts. Bestseller discounting 10 can encourage customer traffic and the purchase of a basket of other products in the same transaction. Although most studies treat retailers as 11 symmetric, the cross-selling potential is generally asymmetric across retailers, since some online retailers have more products to sell. In addition, 12 the cross selling effect works both ways — customers intending to buy a best-seller may buy other items in their shopping basket, while other 13 customers intending to buy a basket may buy a best-seller while visiting the retailer. The authors model the pricing implications of this rich variety 14 of asymmetric cross-selling, with both best sellers and typical baskets acting as traffic generators and cross-sold products. The common wisdom 15 that loss leader pricing leads to neither a significant increase in-store traffic nor an increase in profits does not apply in an asymmetric case where 16 one retailer has more products to cross-sell. The cross-selling potential of products even far down the bestseller list is demonstrated. Empirical 17 analyses provide support for key findings of the theoretical model using book pricing and sales rank data from multiple online retailers.

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with Harald van Heerde and Els Gijsbrechts, Journal of Marketing Research, 52(5), 2015, 674-693

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This article explores how media coverage of a price war affects customer, retailer, and investor reactions over time. Using data covering a Dutch supermarket price war (2003–2005), the authors find that price reductions, especially deep reductions, trigger media coverage of the price conflict. This sets off a chain of reactions. Press messages have a significant effect on market share and abnormal stock returns, beyond retailers’ own price and advertising. Importantly, this study uncovers striking asymmetries regarding the kind of coverage to which stakeholders react: whereas consumers only respond to the tone of price-related press coverage, retailers and investors only react to its quantity. Next, media coverage feeds back into the retailers’ pricing actions: more media coverage triggers new price cuts in addition to those dictated by competitive reactions. As such, media coverage triggers a deeper spiral of price cuts, intensifying the competitive price battle. However, as the price war progresses, media coverage becomes less frequent and less favorable, which decelerates the downward price spiral.

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with P. Kopalle, D. Biswas, P. Chintagunta, J. Fan, B. Ratchford and J. Sills, Journal of Retailing, 85 (1), 56-70, 2009.

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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.

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with E. Gijsbrechts and H. van Heerde, Journal of Marketing Research, 45(5), October, 499-518, 2008, leading articleand finalist for the 2009 Paul Green Award

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Although retail price wars have received much business press and some research attention, it is unclear how they affect consumer purchase behavior. This article studies an unprecedented price war in Dutch grocery retailing that started in fall 2003, initiated by the market leader to halt its sliding market share. The authors investigate the short- and long-term effects of the price war on store visits, on spending, and on the sensitivity of these decisions to weekly prices and price image. They use a unique data set with consumer hand-scan and perceptual data for a national panel of 1821 households, covering two years before and two years after the price war started. Although the price war initially entailed more shopping around and increased spending, spending per visit ultimately dropped because consumers redistributed their purchases across stores. The price war made consumers more sensitive to weekly prices and price image, which helped both the chain that showed an improvement in price image (the price war initiator) and the chains that already had a favorable price image (hard discounters). The price war initiator managed to halt the slide in its market share, and its stock price improved. The losers were the rival mid-level and high-end chains. Unlike the initiator, their price image did not improve, and they suffered from increased price image sensitivity. The authors provide managerial implications for firms that are (or about to be) involved in a price war.

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with Vincent Nijs and Shuba Srinivasan, Journal of Marketing, 72 (March), 15-27, 2008

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The authors develop a conceptual framework of the factors that motivate a retailer’s decision to rely on demand conditions and past prices in setting current and future prices. Specifically, they examine the circumstances under which retailers choose demand-based pricing versus past-price dependence for different brands and categories.  Given scarce resources and costs of price adjustments, demand-based pricing is more likely when the customer-driven and firm-driven costs of adjusting pricing patterns are low or when the benefits of such adjustments are high. First, the customer-driven benefits of demand-based pricing are expected to be greater in categories with higher penetration and for brands with higher market share and higher demand sensitivity to price. Second, the firm-driven benefits are greater for categories with higher private-label share. Finally, the customer-driven costs are greater for expensive categories, whereas the firm driven costs are greater for categories with many stock-keeping units. The empirical findings support the conceptual framework, implying that customer-driven and firm-driven benefits are the main stimulants in the retailer’s choice of demand-based pricing. In contrast, customer-driven and firm-driven costs significantly hinder retailer implementation of demand-based pricing. These insights enable retailers to identify problem areas and opportunities to improve the allocation of scarce pricing resources. The results also contribute to the ongoing debate in economics and marketing on the rationality of observed past-price dependence. Whereas previous research points to the negative impact on gross margins of this practice, the authors find that retailers weigh the costs and benefits of demand-based pricing rather than adhere to past-pricing patterns.

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Journal of Retailing, 83(3), 297-308, 2007, Winner of the 2009 Davidson Best Paper Award.

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While both retailer and competitor decisions contribute to long-term promotional effectiveness, their separate impact has yet to be evaluated. For 75 brands in 25 categories, the author finds that the long-term retailer pass-through of promotions is 65 percent, yielding a long-run wholesale promotional elasticity of 1.78 before competitive response. However, competitors partially match the wholesale price reduction by 15 percent, which decreases promotional elasticity by 10 percent. The range of retailer and competitor response across the analyzed cases is very wide, and is affected by category and brand characteristics. As to the former, large categories yield stronger retailer response, while concentrated categories yield stronger competitor response. As to the latter, smaller brands face a fourfold disadvantage compared to leading brands: they obtain lower retail pass-through, lower retail support, and lower benefits from competing brand’s promotions, while their promotions generate higher benefits to competitors. Interestingly, the mid-1990s move from off-invoice allowances towards scan back deals only partially improves their promotional effectiveness compared to that of leading brands.

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with Shuba Srinivasan and Vincent Nijs, Marketing Science, 26(4), 473-487, 2007

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What are the drivers of retailer pricing tactics over time? Based on multivariate time-series analysis of two rich data sets, we quantify the relative importance of competitive retailer prices, pricing history, brand demand, wholesale prices, and retailer category-management considerations as drivers of retail prices. Interestingly, competitive retailer prices account for less than 10% of the over-time variation in retail prices. Instead, pricing history, wholesale price, and brand demand are the main drivers of retail-price variation over time. Moreover, the influence Of these price drivers on retailer pricing tactics is linked to retailer category margin. We find that demand-based pricing and category-management considerations are associated with higher retailer margins. In contrast, dependence on pricing history and pricing based on store traffic considerations imply lower retailer margins.

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with Shuba Srinivasan and Philip-Hans Franses, Marketing Science, 26(1), 83-100, 2007.

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Marketing literature has long recognized that brand price elasticity need not be monotonic and symmetric, but has yet to provide generalizable market-level insights on threshold-based price elasticity, asymmetric thresholds, and the sign and magnitude of elasticity transitions. This paper introduces smooth transition regression models to study threshold-based price elasticity of the top 4 brands across 20 fast-moving consumer good categories. Threshold-based price elasticity is found for 76% of all brands: 29% reflect historical benchmark prices, 16% reflect competitive benchmark prices, and 31% reflect both types of benchmarks. The authors demonstrate asymmetry for gains versus losses on three levels: the threshold size and the sign and the magnitude of the elasticity difference. Interestingly, they observe latitude of acceptance for gains compared to the historical benchmark, but saturation effects in most other cases. Moreover, category characteristics influence the extent and the nature of threshold-based price elasticity, while individual brand characteristics impact the size of the price thresholds. From a managerial perspective, the paper illustrates the sales, revenue, and margin implications for price changes typically observed in consumer markets.

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with S. Srinivasan, D.M. Hanssens and M. Dekimpe, Management Science, 50 (5), 617-629, 2004.

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Do price promotions generate additional revenue and for whom? Which brand, category, and market conditions influence promotional benefits and their allocation across manufacturers and retailers? To answer these questions, we conduct a large-scale econometric investigation of the effects of price promotions on manufacturer revenues, retailer revenues, and total profits (margins). A first major finding is that a price promotion typically does not have permanent monetary effects for either party. Second, price promotions have a predominantly positive impact on manufacturer revenues, but their effects on retailer revenues are mixed. Moreover, retailer category margins are typically reduced by price promotions. Even when accounting for cross-category and store-traffic effects, we still find evidence that price promotions are typically not beneficial to the retailer. Third, our results indicate that manufacturer revenue elasticities are higher for promotions of small-share brands, for frequently promoted brands and for national brands in impulse product categories with a low degree of brand proliferation and low private-label shares. Retailer revenue elasticities are higher for brands with frequent and shallow promotions, for impulse products, and in categories with a low degree of brand proliferation. Finally, retailer margin elasticities are higher for promotions of small-share brands and for brands with infrequent and shallow promotions. We discuss the managerial implications of our results for both manufacturers and retailers.

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with D.M. Hanssens and S. Siddarth, Journal of Marketing Research, vol. 34 (November), 421-439, 2002. Winner of the O’Dell Award 2007.

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To what extent do price promotions have a long-term effect on the components of brand sates, namely, category incidence, brand choice, and purchase quantity? The authors answer this question by using persistence modeling on weekly sales data of a perishable and a storable product derived from a scanner panel. Their analysis reveals, first, that permanent promotion effects are virtually absent for each sales component. Next, the authors develop and apply an impulse response approach to estimate the promotional adjustment period and the total dynamic effects of a price promotion. Specifically, they calculate the long-term equivalent of Gupta’s (1988) 14/84/2 breakdown of promotional effects. Because of positive adjustment effects for incidence but negative adjustment effects for choice, the authors find a reversal of the importance of category incidence and brand choice: 66/11 /23 for the storable product and 58/39/3 for the perishable product. The authors discuss the implications of the findings and suggest some areas for further research.

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