Similarity-Based Spatial Methods to Estimate Shelf Space Elasticities

A retailer may allocate shelf space to brands based on factors, unobservable to researchers, which also determine sales. As a consequence, both sales and shelf space are endogenous in historical data, and this leads to inconsistent estimates of shelf space elasticities based on OLS. To obtain valid estimates of shelf space elasticities for allocation decisions, we propose an approach that incorporates the spatial correlation between shelf space and the error term resulting from store-, consumer- and competitor characteristics. The empirical results suggest that our model based on a single cross section of stores corrects for endogeneity and provides valid shelf space elasticities. We also obtain superior predictions compared to several benchmark models. With the same cross section and two observations over time, the alternative methods we use provide comparable shelf space elasticity estimates. However, our proposed method is still superior in the sense that its estimates have somewhat smaller standard errors.     

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.     

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.     

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.     

Patterns of consumer response to retail price differentials

Decomposing price elasticity suggests that the major impact of promotions is on brand switching rather than increased consumption. Consumers may also buy smaller quantities of more expensive brands when compared to cheaper ones (inter-brand elasticity). Using panel data for the purchases of 80 consumers buying nine product categories over a 16-week period, we verified that inter-brand elasticities occur, and report the relative importance of intra- and inter-brand elasticities in determining quantity price elasticity per shopping occasion for the product category. Brands were classified by informational (socially mediated) and utilitarian (product-mediated) benefits. Intra-brand elasticity was higher than utilitarian inter-brand elasticity, which was higher than informational inter-brand elasticity.     

A NOTE ON TRADE ELASTICITIES IN ASIAN COUNTRIES

This article estimates the price and income elasticities of import and export demands for India, Japan, the Philippines, Sri Lanka, and Thailand using annual time series data. Both price and income elasticities of import demand are found to be in the inelastic range for all five countries. Export demand is found to be price elastic for Japan, the Philippines, and Thailand and price inelastic for India and Sri Lanka. Export demand is found to be income elastic for Japan but not for the other four countries. The Marshall-Lerner-Robinson condition states that a devaluation improves the balance of trade position only if the sum of the absolute values of price elasticity of import demand and the price elasticity of export demand is greater than one. This condition is met for India, Japan, the Philippines, and Thailand but not for Sri Lanka.     

Understanding interstate trade patterns

This paper models and estimates bilateral trade patterns of U.S. states in a CES framework and identifies the elasticity of substitution across goods, the elasticities of substitution across varieties of each good, and the good-specific elasticities of distance by using markup values obtained from the production side. Compared to the international trade literature, the elasticity of substitution estimates are lower across both goods and varieties, while the elasticity of distance estimates are higher. Although home-bias effects at the state level are significant, there is evidence for decreasing effects over time.     

Using the Pack‐and‐a‐Half Rule to Eliminate Backroom Inventories in Retail Operations

In the retail industry, backroom inventories are typically associated with higher labor costs and greater operational complexity. Thus, retailers look for ways to eliminate backroom inventories. A heuristic used for this purpose is the pack‐and‐a‐half rule which suggests that the shelf space allocated for a product should be at least 50% larger than the case pack quantity in which the product is delivered. Despite its popularity among retailers, the pack‐and‐a‐half rule has been ignored in the academic literature. We introduce the pack‐and‐a‐half rule, assess its impact on a retailer's profits, identify cost, demand, and product characteristics driving this impact, and propose a modification. Based on an analysis of data obtained from a retailer on 1,986 SKUs in 20 categories, we find that the pack‐and‐a‐half rule decreases a retailer's profits, on average, by 10% when applied uniformly across all SKUs. Further, this decrease is significantly affected by product depth, product width, demand elasticity, case pack quantity, and inventory carrying cost. Finally, we develop a set of modifications based on these variables where the pack‐and‐a‐half rule is applied selectively and in a stepwise fashion. These modifications limit the decrease in a retailer's profits to a range between 6% and 7%.     

Does shelf space management intervention have an effect on calorie turnover at supermarkets?

Despite recognizing the potential of retail settings for interventions aimed at bringing the rate of obesity down, there have been few attempts to implement experimental studies aiming to increase consumption of healthy foods and decrease consumption of unhealthy foods in the retail setting. An experimental controlled trial has been conducted using 10 supermarkets in Denmark. The study looked specifically into the possible effect of shelf space management intervention at supermarkets. The study found a significant intervention effect for individual products targeted by the project. But overall, care is needed to interpret results on aggregate level since statistical findings do not support category wide effect of shelf space intervention.     

The Impact of Omitting Promotion Variables on Simulation Experiments

Using store-level scanner data, elasticity matrices are estimated using a twotiered demand system. Two basic models are estimated, one with promotion variables and one without. Differences between the estimates across the two models are statistically significant. However, when the elasticities are used as 'inputs' into several simulation exercises, there are only small differences in merger effects and patent damage estimates.The results suggest that the differences are not 'economically' significant.     

Prices and promotions in U.S. retail markets

We provide generalizable results on the price and promotion tactics employed in the U.S. retail grocery industry. First, we document a large degree of price dispersion for UPCs and brands across stores, both nationally and at the local market level. Base price differences across stores and price promotions contribute to the overall price variance, and we show how to decompose the price variance into base price and promotion components. Second, we document that a large percentage of the variation in prices and promotion tactics across stores can be explained by retail chain and especially market/chain factors, whereas market factors explain only smaller percentage of the variation. Third, we show that the chain-level price and promotions similarity can be explained by similarity in demand. In particular, a large percentage of the variance in price elasticities and promotion effects can be explained by retail chain and especially market/retail chain factors. Further, price elasticities and promotion effects across stores of the same chain are hard to distinguish from the chain-market-level mean, and cross-price elasticities are typically imprecisely estimated. These findings suggest that retail managers may plausibly consider price discrimination across stores to be infeasible.

     

How Online Product Reviews Affect Retail Sales: A Meta-analysis

A growing body of research has emerged on online product reviews and their ability to elicit performance outcomes desired by retailers; yet, a common understanding of the performance implications of online product reviews has eluded us. Scholars continue to navigate an array of studies assessing different design elements of online product reviews, and various research settings and data sources. We undertake a meta-analysis of 26 empirical studies yielding 443 sales elasticities to examine how these variables relate to retail sales. Building on well-established meta-analytical methods, we address the following questions: How does review valence influence the elasticity of retailer sales? What about review volume? For which product types and usage situations do online product reviews have a greater impact on retailer sales elasticity? Which types of online reviewers and websites exert the greatest influence on retailer sales elasticity? Our study answers these important questions and provides a much needed quantitative synthesis of this burgeoning stream of research.     

Distributional Effects of Lower Food Prices in a Rich Country

Controlling for differences in taxes and transportation costs, the Nordic Competition Authorities claims, in a report from 2005, that food prices are 11% higher in Sweden compared to the EU-15 countries. One explanation for this put forward in the report is the limited competition on this market which suggests there to be a potential for lower food prices. This paper focuses on distributional effects of a price decrease on food. Based on a simple model of household utility, the households demand for food is derived and estimated. Price and income elasticities for different income groups are then calculated based on these parameter estimates. Our results suggest that food is a normal good with an average income elasticity of approximately 0.18 and a price elasticity of 0.45. In addition, and of importance from a policy perspective, the results indicate the income elasticity to differ across income groups while price elasticities are constant.     

A cross-sectional analysis of asset holdings

This article introduces cross-sectional data on asset holdings derived from a survey of Australian households. We use the data to estimate asset Engel curves which are shown to fit the data extremely well. The findings indicate that cash and bank deposits and insurance are necessities, with wealth elasticities less than unity, own home has an elasticity of one and the other four assets [1) other property, 2) shares and securities, 3) superannuation, and 4) unincorporated business] are luxuries with wealth elasticities greater than unity. The Engel curve estimates are used to explain differences in the dispersion of the portfolio across households and to compute a measure of the substitutability complementarity between the individual assets. The results indicate that 1) housing is a substitute for all other assets and 2) business related assets are all pairwise complements.     

World-wide effects and import elasticities

This paper shows that estimates of import demand elasticities will be biased towards zero from the exclusion of any variable that has internationally common or world-wide effects. This is true for both demand- and supply-affecting variables. The bias from world-wide effects is demonstrated in conjunction with the bias from mismeasured prices and quantities. It is shown that the true price elasticity can be bounded by the regression of quantities on prices and of prices of quantities. Estimates are presented on the range within which the true values lie. It is shown that the true import demand elasticities could be very large.     

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 impact of location factors on the attractiveness and optimal space shares of product categories

In this paper, we investigate the impact of location characteristics on the relative attractiveness of product categories within a store, and formulate micromarketing implications for the allocation of store space to categories. We present a framework for the impact of store and trading area characteristics on category and store performance, which integrates and extends previous geomarketing research. Building upon this framework, we propose a tractable and flexible procedure for assessing location influences, and derive optimal space allocation rules for different location profiles. Empirical application to national stores of a European retail chain confirms the differential impact of location characteristics on categories' attractiveness. Tailoring the allocation of store space to these location-based differences in category appeal leads to a significant increase in overall chain profitability.     

Predicting Under- and Overperforming SKUs within the Distribution–Market Share Relationship

This research presents a retail analytics application which uses machine learning (ML) to identify and predict under- and overperforming consumer packaged goods (CPGs) using retail scanner data. Essential to measuring market performance at the SKU level is the relationship between distribution and market share (the velocity curve). We validate that ML can reproduce the velocity curve, and ML is further used to predict underperforming, in-line performing, and overperforming SKUs relative to the velocity curve, based on a range of variables (SKU features) at a point in time. Our ML approach can correctly predict 83% of SKUs as under-, in-line-, or overperforming based on their characteristics. The research analyzes 9,321 SKUs of 2,565 brands across seven product categories of CPGs which were sold in 8,117 stores from 49 different retail chains of five different retail channels located in the US states of California, New York, Texas, and Wisconsin. The retail stores comprise convenience stores, drug stores, food stores, liquor stores, and mass merchandise retail stores. The data is Nielsen retail store scanner data for the calendar year 2014. The relationship between distribution and market share is a market-wide proxy for the ratio of relative sales in a category to, for example, aggregate shelf space, a key retail productivity metric. We further find indications that the distribution of SKUs across different store sizes, the stores’ category specialization, the line length of the brands, the overall performance of the parent brand, and sales consistency are the most important characteristics for the prediction of market share performance beyond the velocity curve. The methods and results presented will help CPG marketers (suppliers and retailers) understand which SKUs are under-, in-line-, or overperforming and the potential factors contributing to that performance. Optimizing assortments and portfolios is essential to decrease failure rates of individual SKUs. ML approaches can evolve to complementary support tools for such management problems.     

Estimates and Determinants of Armington Elasticities for the U.S. Food Industry

This paper provides estimates of elasticities of substitution between domestic and imported goods for 40 4-digit S.I.C. food manufacturing industries and explains the inter-industry differences among these coefficients in terms of industry sectoral characteristics. The results show that there is a wide range of variation among such elasticities and that the intensity of each industrys percentage of output sold to final consumers, foreign direct investment, expenditures on advertising and the existence of import quotas affect the degree of substitutability between domestic and foreign goods in the face of a relative price change.     

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.