Shelf space elasticity: A meta-analysis

This article presents a meta-analysis of 1,268 estimates of shelf space elasticities, that is, the ratio of additional sales to additional space allocated in retail settings. The study finds several new empirical generalizations about shelf space elasticity. The most important generalizations are as follows: The average observed shelf space elasticity is .17, which varies across product categories, with the lowest estimates for commodities, followed by staples, and the highest estimates for impulse buys. Store size moderates the effect of product characteristics on shelf space elasticity: in large stores, the difference between elasticities for brand versus category is greater than in small stores. Furthermore, the shelf space elasticity estimates are less dependent on method characteristics than commonly assumed in the literature. Regarding the influence of the direction of space variation, the study finds that shelf space increases results in greater elasticity estimates than shelf space reduction, a finding that emphasizes the application of shelf space variation as a useful marketing tool. These findings provide several implications for managers and researchers.     

Estimation of product category sales responsiveness to allocated shelf space

A retail chain manager must draw on experience based on data available from his points of sale to diagnose space misallocations in stores and to make recommendations. This paper presents an empirical estimate of shelf space elasticities from a variety store chain database at product category level with a share of space vs. share of sales econometric model. It suggests that external influences could explain space elasticity differences. Results show that space elasticities increase with the impulse buying rate of the product category and do not depend on the type of store.     

Which Brands Gain Share from Which Brands? Inference from Store-Level Scanner Data

Market share models for weekly store-level data are useful to understand competitive structures by delivering own and cross price elasticities. These models can however not be used to examine which brands lose share to which brands during a specific period of time. It is for this purpose that we propose a new model, which does allow for such an examination. We illustrate the model for two product categories in two markets, and we provide share-switching estimates. We also demonstrate how our model can be used to decompose own and cross price elasticities.JEL Classification: C10, C51, C53, M31     

DIRECT PRODUCT PROFITABILITY AND RETAIL SHELF‐SPACE ALLOCATION MODELS

Given an assortment of k products, a retailer must make an important decision on the percentage of space allocated to each of them. Optimization models for this problem have previously shown that an item's space should not simply be given in proportion to its sales or its gross margin (GM). Calculations of Direct Product Profitability (DPP) have improved upon the GM concept, but the present paper is the first (of which we are aware) to integrate the DPP approach into a shelf‐space optimization model.     

The different faces of coupon elasticity

Coupons account for over two-thirds of all consumer promotional efforts initiated by the manufacturers of consumer goods. In this study, the impact of coupons on brand sales is investigated and how that impact decays over the life of the coupon is demonstrated. Specifically, we present an econometric model that can capture coupon effects in terms of equivalent price reduction, account for coupon effects over time, allow inference of coupon effects when retailers decide to double or triple the coupon value, and provide both self-coupon and cross-coupon elasticities at different levels of aggregation. A widely used sales response model is adapted, and an analytical model is proposed to estimate both the self-coupon and cross-coupon (face value) elasticities of sales at the store level. From the store-level elasticity estimates for a given week, the authors analytically derive the coupon elasticities for the chain level by aggregating across stores, and over the life of the coupon by aggregating over time. The proposed sales response model is estimated with the data obtained from three markets for various product categories, and the coupon elasticities are computed. The proposed framework allows one to demonstrate the hypothetical equivalence of a shelf-price reduction for a given coupon face value in each week. Also, the effect of doubling the face value of a coupon results in more than a proportionate increase in elasticity. The authors find that both self and cross-coupon elasticities are much smaller in magnitude than the average self and cross-price elasticity measures reported in the literature.     

Understanding the Characteristics of Price Elasticities for Frequently Purchased Packaged Goods

This study examines category and brand level factors of packaged goods to determine which ones are related to brand price elasticities. A new nonparametric method of elasticity calculation is presented that is suited to situations where detailed feature and display information is not available. To obtain results that lead to strong and reliable generalisations, we examine 26 categories and 110 brands using store level weekly scanner data. We also synthesise our results with four previous studies that have looked at determinants of price elasticities. Three factors consistently emerge as important drivers of elasticity. They are, competitive intensity in the category, whether or not the product is storable and the brand market share. A further, less certain, factor is the frequency of promotion activity, with categories and brands having more frequent promotions exhibiting lower sales increases when one or more of the brands price promotes.     

Estimation of meat demand system in Jordan: an almost ideal demand system

This paper reports the results of the estimation of a linear approximate almost ideal demand system for Jordan meat demand using cross‐sectional data collected by the Department of Statistics in Jordan as part of the household expenditure survey. A censored regression method for the system of equation is used to analyse the meat consumption patterns. This method allows for inclusion of a large number of zero consumption for some foods. Two‐step demand system was estimated. In the first stage, Inverse Mill Ratio is estimated by using probit regression model. In the second stage, the estimated variable is included in the AIDS model to estimate food demand elasticities. The objective of this work is to provide econometric estimates of the different types of demand elasticities for meats in Jordan. To be consistent with the demand theory, the homogeneity, symmetry and adding up restrictions were satisfied in the estimated models. The estimated model was used to obtain estimates of Hicksian, Marshallian and expenditure demand elasticities for meats in Jordan. The results revealed that the demand for mutton and poultry is elastic while the demand for beef and fish is inelastic. The cross‐price elasticities indicate that poultry and beef are substitutes to mutton. The expenditure elasticities confirm that beef and mutton are luxury goods while poultry and fish are necessity goods.     

The Impact of Advertising on Consumer Demand for Beef:

Thi study used two related data sets to obtain new estimates of food shopper responses to prices and advertising. Supermarket scan data comprised the source of information of sales and prices. Chain level newspaper and broadcast media advertising in the area measured the marketing program. Unique features of the study include the use of item movement and the accomodation of possible cross media effects. Consequently, the paper presents a way of monitoring promotions and relating them to sales. Three fresh beef aggregates (ground, roasts, and steaks) are used to estimate the impacts of broadcast media and newspaper adevertising by a supermarket chain. New estimates of direct and cross advertising impacts are also reported.     

Cross channel effects of search engine advertising on brick & mortar retail sales: Meta analysis of large scale field experiments on Google.com

We investigate the cross channel effects of search engine advertising on Google.com on sales in brick and mortar retail stores. Obtaining causal and actionable estimates in this context is challenging: Brick and mortar store sales vary widely on a weekly basis; offline media dominate the marketing budget; search advertising and demand are contemporaneously correlated; and estimates have to be credible to overcome agency issues between the online and offline marketing groups. We report on a meta-analysis of a population of 15 independent field experiments, in which 13 well-known U.S. multi-channel retailers spent over $4 Million in incremental search advertising. In test markets category keywords were maintained in positions 1-3 for 76 product categories with no search advertising on these keywords in the control markets. Outcomes measured include sales in the advertised categories, total store sales and Return on Ad Spending. We estimate the average effect of each outcome for this population of experiments using a Hierarchical Bayesian (HB) model. The estimates from the HB model provide causal evidence that increasing search engine advertising on broad keywords on Google.com had a positive effect on sales in brick and mortar stores for the advertised categories for this population of retailers. There also was a positive effect on total store sales. Hence the increase in sales in the advertised categories was incremental to the retailer net of any sales borrowed from non-advertised categories. The total store sales increase was a meaningful improvement compared to the baseline sales growth rates. The average Return on Ad Spend (ROAS) is positive, but does not breakeven on average although several retailers achieved or exceeded break-even based only on brick and mortar sales. We examine the robustness of our findings to alternative assumptions about the data specific to this set of experiments. Our estimates suggest online and offline are linked markets, that media planners should account for the offline effects in the planning and execution of search advertising campaigns, and that these effects should be adjusted by category and retailer. Extensive replication and a unique research protocol ensure that our results are general and credible.     

Substitution or Promotion? The Impact of Price Discounts on Cross-Channel Sales of Digital Movies

Technology is transforming the marketing function in many ways, and this transformation is particularly apparent for information goods such as movies where digital technologies provide marketers with new distribution channels, which in turn create new opportunities for cross-channel effects. However, these digital channels also provide researchers with new opportunities to measure micro-level customer behavior to understand the impact of cross-channel effects in real-world settings.In this paper, we study cross-channel effects between movies sold in digital purchase (commonly known as Electronic Sell Through or EST) and digital rental (commonly known as Video-On-Demand or VOD) markets. We do this using a unique sales dataset from a major digital movie retailer provided by a major movie studio. Our analysis takes advantage of a 14-week field experiment that allows us to measure the impact of price discounts on own- and cross-channel sales. We use this experiment to estimate own and cross price elasticities, whether price discounts cannibalize future sales, and most importantly whether price discounts in one channel affect sales for the same product in a presumably competing channel.Our analysis indicates that digital movie consumers are highly sensitive to price promotions. However, we also find that, contrary to expectations, price promotions in a digital sales channel for a movie do not seem to cannibalize digital rentals. Indeed, our results suggest that, if anything, price promotions for digital movie sales can increase digital rentals. We explore a variety of explanations for this counterintuitive result, including the possibility that the ease of information transmission online through third-party websites, blogs, and online discussion areas may create information spillovers such that price discounts in one channel may increase product awareness in other competing sales channels. From a managerial perspective, our results suggest that cross-channel cannibalization can be reduced or even reversed in the presence of information spillovers, and that there are many new opportunities for marketers to directly measure these cross-channel effects using experimental data from online platforms.     

Consumer learning, switching costs, and heterogeneity: A structural examination

This paper develops and estimates a model of forward-looking consumer learning with switching costs using household level scanner data from a frequently purchased product category. This is novel because current models of consumer purchase behavior assume that only one of these types of dynamics is present, not both at the same time. My model estimates support the presence of both learning and switching costs in this product category. The estimates show that before consuming new products, consumers are unsure of their tastes for them, and subsequently learn their tastes by purchase and consumption of new products. Switching costs are large, comprising roughly 30 percent of the cost of a medium sized package of the product. Additionally, the model incorporates very rich individual level unobserved heterogeneity in price sensitivities, tastes, and switching costs, and the amount by which consumers learn. To show that my model produces different implications than a model with learning or switching costs only, I estimate two more specifications, one without each type of dynamics, and simulate counterfactuals that are of interest to managers and policymakers. I find that intertemporal elasticities are underestimated when either type of dynamics is left out, by as much as 90%. Informative advertising is also affected by the presence of switching costs, although the direction of the bias is not signed. Leaving out dynamics also has a large impact on long-term elasticities, which are used by antitrust policymakers to evaluate the impact of mergers. When learning is ignored, cross elasticities are underestimated by as much as 45%. When switching costs are ignored, both own and cross elasticities are underestimated.     

The Effect of Shelf Space on Sales of Fruit Beverages

Abstract

Fruit beverage demand is related to prices, store size, shelf space allocation, and out-of-stock occurrences. A double log demand model is used to estimate the marginal impact of shelf space reallocation on fruit beverage sales. The estimated marginal impacts are compared with the per linear foot average revenue differences among five beverage groups. Results show that differences of average revenue are different from the marginal impacts estimated in this study. Hence, the average revenues are not good measures to be used as a guide for shelf space reallocation.     

Evaluating store location and department composition based on spatial heterogeneity in sales potential

In this paper, we extend a retail location evaluation model with the possibility to include the effect of department size adaptation at the store level. We relate department-level store sales to a store's competitive and demographic environment, thereby providing richer insights into the drivers of department sales than a model of just aggregate sales. Further, we accommodate heterogeneity in consumer characteristics over space by using zip code level data and unobserved spatial effects in department sales by including spatially autocorrelated error terms.Using spatial panel data for 30 clothing stores belonging to one Dutch retail chain, we demonstrate how to use the modeling approach to analyze and predict sales performance of new and existing stores. We show that the predictive performance of our model is superior to that of a benchmark model that does not include spatial autocorrelation.     

Free Trade Agreements In the Americas: Are the Trade Effects Larger than Anticipated?

This paper argues that the ‘competitive liberalisation’ of national governments of the past several decades reflects national governments’ expectations of larger trade impacts from regional economic integration agreements (EIAs) than typical ex ante economic models have suggested. Moreover, we show that previous (typically cross‐section) ex post empirical evaluations of the effects of EIAs on trade have seriously over‐ or underestimated the effects, partly due to ignoring the (endogenous) self‐selection bias of country pairs into EIAs. Accounting for this bias, we find that economic integration agreements in the Americas have had much larger impacts on trade over the period 1960–2000 than previously found and the ex post estimates are less fragile than those in earlier cross‐section analyses. The results shed further light on understanding the causes and consequences of the growth of regionalism in the world.     

Modifying Conjoint Methods to Model Managers' Reactions to Business Environmental Trends: An Application to Modeling Retailer Reactions to Sales Trends

This article proposes and demonstrates how conjoint methods can be adapted to allow the modeling of managerial reactions to various changes in economic and competitive environments and their effects on observed sales levels. Because in general micro-level data on strategic decision making over time are difficult and expensive to obtain, this approach can be of much value to the further study of managerial strategic behavior and market dynamics. In our application we model retailer reactions to changes in their sales, focusing in particular on the actions that affect the demand for retail space and possibilities to improve retail sites. Choice responses to hypothetical sales and environmental trend scenarios are collected from 183 retailers and used to estimate to logit regression model that predicts retailers' probabilities of choosing actions. The model results confirm that retailers are more likely to take action when sales go down than when they go up, and also that they react more quickly if sales go down. It is also found that retailers are more reluctant to change the positioning of their store when confronted with a sales increase than when confronted with a sales decrease. The model is compared with a non-experimental model that is based on retailers' reactions to the trends they report to have observed for their own stores. The article concludes with a discussion of the implications of this research for the further development of conjoint-like approaches to studying entrepreneurial behavior.     

Estimating the Cost‐of‐Equity Capital Using Empirical Asset Pricing Models

Empirical asset pricing models seek to capture characteristic‐based patterns in the cross‐section of average stock returns. I propose a new approach for constructing these models, and investigate its performance with respect to estimating the cost‐of‐equity capital. Using a model that accounts for the cross‐sectional relation between five characteristics and average stock returns, I obtain cost‐of‐equity estimates that outperform those produced by the Fama‐French five‐factor model in out‐of‐sample tests. Because the proposed approach builds directly on standard cross‐sectional regression techniques, it provides complete flexibility in choosing the firm characteristics used to formulate the cost‐of‐equity estimates.     

Coercion in the selling of credit life insurance

Credit life insurance, which repays some or all of a borrower's outstanding debt in the event of death, has been a controversial subject for many years. Critics assert that, despite regulations that limit tied sales, pressure on loan officers to generate fee income through cross selling creates an incentive for coercion of borrowers. Allegedly, some sales techniques leave the consumer with the false impression that the purchase of credit insurance was necessary to obtain the loan. This article measures the frequency with which creditor efforts to sell credit insurance transform the sales message from persuasive to coercive. A methodology is developed for measuring the impact of coercive selling pressure applied to borrowers at the point of sale. Data used to measure the effect of coercive pressure are taken from an extensive survey of borrowers conducted during 1993. Not only are public policy concerns about coercion in the selling of credit insurance addressed, but more generally the article offers a methodology to quantify the influence of the customer's point-of-sale experience on the decision to purchase any financial service. © 1995 John Wiley & Sons, Inc.     

Credit constraints and firm export: Microeconomic evidence from Italy

This paper estimates the impact of credit rationing on firms' export. We use detailed survey data from Italian manufacturing firms that provide a firm-specific measure of credit rationing based directly on firms' responses to the survey rather than indirectly on firms' financial statements. After controlling for productivity and other relevant firm attributes, and accounting for the endogeneity of credit rationing, we find that the probability of exporting is 39% lower for rationed firms and that rationing reduces foreign sales by more than 38%. While credit rationing also appears to depress domestic sales, its impact on foreign sales is significantly stronger. The analysis also suggests that credit rationing is an obstacle to export especially for firms operating in high-tech industries and in industries that heavily rely on external finance.     

Omnichannel marketing: Are cross-channel effects symmetric?

The rapid growth in omnichannel (e.g., Web, call center, sales agent, store) shopping and the need to effectively allocate resources across channels are prompting managers and researchers to better understand cross-channel effects, that is, the effects of marketing efforts in one distribution channel on shopping outcomes in other channels. We develop a broad set of hypotheses about cross-channel effects based on channel richness and influence roles (informative, persuasive). To test the hypotheses, we model the effects (own and cross) of channel marketing efforts on shopping outcomes in different channels through a simultaneous equation system. We estimate these models using data from the auto insurance industry that comprises the exclusive agent, the independent agent, the Web, and the call center channels. Our results offer novel insights. They show that cross-channel effects and elasticities are significant and asymmetric. While the effect of marketing efforts in a channel on shopping outcomes in a dissimilar (with a different primary influence role) channel is positive (e.g., exclusive agent, the Web, and the call center channels are complementary), the magnitudes of the cross-channel effects are asymmetric. Similarly, while the effect of marketing efforts in a channel on shopping outcomes in a similar (with the same primary influence role) channel is negative (e.g., independent agent and exclusive agent channels are substitutional), they are also asymmetric. Exclusive agent efforts have a greater negative effect on the outcomes of independent agent efforts than vice versa. Based on the results, we develop a channel influence vs. influenceability analysis tool for managers to better plan their channel efforts. We also illustrate a resource allocation model that shows substantial incremental profits from the reallocation of marketing efforts based on our model with cross-channel effects relative to a model without cross-channel effects.     

LOGISTICS AND ASSORTMENT DEPTH IN THE RETAIL SUPPLY CHAIN: EVIDENCE FROM GROCERY CATEGORIES

Managing the logistical issues resulting from changes in assortment depth in the retail supply chain is challenging, involving various complex tradeoffs. While increasing assortment depth can increase sales, it also increases inventory‐holding costs and reduces the amount of space for other items. As space is taken from existing items to increase assortment depth, it reduces the inventory‐holding capacity of existing items on the shelf, increasing expected annual cost of lost sales. The paper presents a conceptual model of the relationships between assortment depth, category gross margins, and the logistical concerns resulting from inventory costs and out‐of‐stocks. Evidence for the significance of depth and resulting costs are provided in an examination of 100 product categories from a case study of a retail grocery chain.