The impact of a gasoline crisis on retail sales

The gasoline crises of the 1970s demonstrated the need for including gasoline prices and gasoline shortages in models explaining retail sales. In this article, a model is constructed that incorporates the aforementioned variables, other variables, and a lagged sales figure as independent variable. The results indicate a high degree of explanatory power in predicting retail sales for a specialty store chain with a preponderance of their stores in large regional malls that sell a product which lends itself to unplanned purchase behaviour.     

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.     

中国实体零售企业运营效率及其影响因素研究——基于随机前沿分析方法

近年来，零售产业发生较大变化，实体零售企业纷纷关闭门店收缩经营，探讨新时期实体零售企业运营效率水平及其影响因素具有现实意义。文章利用2007—2016年实体零售企业门店调查问卷数据，采用随机生产前沿和随机成本前沿等不同模型，检验营业面积和员工数量两种投入要素情况下的零售企业生产函数特征，例如规模报酬效应、产出弹性以及规模经济效应等，同时检验实体零售门店商圈竞争度、门店经营历史、商品周转天数、日交易量和客单价等因素对门店运营效率的影响效应。结果发现，我国实体零售企业处于规模报酬不变阶段，专卖店和百货店的运营效率较高，而超市和购物中心的运营效率较低；以及门店经营历史、日交易量和客单价对门店运营效率具有正向影响。最后针对实体零售企业门店经营决策提出管理建议。     

Influence of retail store environmental cues on consumer patronage behavior across different retail store formats: An empirical analysis of US Hispanic consumers

This study examined the influence of Hispanic consumers’ perceived importance of apparel retail store environmental cues and demographic characteristics (i.e., age and the number of years lived in the US) on their apparel store patronage behavior across various retail store formats. Three apparel retail store environmental cue dimensions were identified. Of the three dimensions, Customer Service appeared as a significant determinant in Hispanic consumers’ decision to shop at department stores, specialty stores, and mass merchant stores. Convenience was significantly, but negatively, related to the use of specialty stores. Physical Atmosphere appeared as significant determinants of Hispanic consumers’ use of Internet websites. The respondents’ shopping frequency at department stores, Internet websites, and catalogues was significantly different based on the respondents’ age and number of years lived in the US This study offers insights for apparel retailers in building effective retail store environments to attract Hispanic consumers.     

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.     

Flatlined: Combatting the death of retail stores

The recent wave of retail bankruptcies as well as poor sales performance has resulted in a large number of store closings. Low sales in store-based retailers can also be attributed to the rapid growth of web-based retailers (largely, Amazon) as well as an excess of store space per capita in the U.S. as compared to other developed nations. Strategies to stem the decline of retail stores include: (1) utilizing omnichannel-based synergies among channels and devices to increase store sales; (2) making stores more attractive and engaging through personalization, interactivity, and a constantly changing environment; and (3) improving productivity through introducing small-size store formats and downsizing existing stores.     

Retailing strategy for customer growth and new customer attraction

The image that current and potential customers have of a retail store affects the magnitude of patronage at that store. In attempting to increase store patronage, management of a retail store must look to people who already are customers, as well as to people who are not current customers. The appropriate strategy depends upon the dimensions used by people in their evaluation of the store. The hypothesis is tested that the strategy used for gaining increased patronage from customers may have to differ from that used to gain patronage from noncustomers.Field survey techniques were used to collect data from 225 adult females. Respondents evaluated three large retail department stores, which were believed to have distinct images in the minds of female shoppers, on the basis of a set of 12 semantic scales that represented various store attributes. Each respondent indicated frequency of shopping at each store. The data were analyzed by two different multiple discriminant analyses. For the customer growth strategy, the semantic scale measures were used to develop a discriminant model for each store to determine which attributes would be the best predictors of shopping frequency. The analysis relevant to the strategy of new customer attraction differed. First, shoppers were classified as loyal to one store on the basis of their rates of shopping at each store. Second, the 36 attribute measurements (12 scales for 3 stores) were factor analyzed, and three factors were extracted. Those attributes which loaded highest on each of the factors for each store were used as predictor variables in the discriminant analysis.The results of this study indicate that different marketing strategies may be required for increasing sales to existing customers and attracting new customers. In addition, consumers do not necessarily differentiate similar type retail stores on the same dimension.     

The impact of weather on consumer behavior and retail performance: Evidence from a convenience store chain in China

Despite extensive use of weather data to adjust replenishment and inventory strategies in the retail industry, these companies do clearly know the effect of weather on consumer behavior and retail performance. How does weather affect consumers' purchasing behavior and thus retail performance? We study empirically these questions by analyzing more than 6 million transactions made by more than 1.62 million unique consumers at 146 convenience stores in a convenience store chain in China. We choose sun, rain, temperature, and air quality index as the main weather variables. We use the average number of items per order and the average price of each item in each order as indicators of consumer behavior, and use store daily sales as an indicator of retail performance. We found that under rainy weather, people will buy more products with higher item prices in one order. When temperature rises, people will buy fewer products with a lower item price in one order. In addition, sunny weather and rainy weather have a positive impact on daily sales than cloudy weather. Air quality has a negative impact on daily sales, while temperature has a positive impact on sales. Finally, we study the impact of weather on different product categories. We find that the results depend on the product category characteristics.     

Chain-wide and store-level analysis for cross-category management

When planning and implementing their price-promotions strategy, retail chain managers face the typical dilemma of “thinking globally, but acting locally.” In other words, they must plan their strategy, keeping in mind the global chain-level impact of their promotions, to deliver on the commitments made to manufacturers. At the same time, managers need to make sure that the implementation of such strategy takes into account the fact that each store caters to a different market with different needs and responses to marketing programs. Moreover, the retail chain manager must consider not only how the promotion of a brand affects competing brands and total category sales, but also how it could affect sales in other categories.Our proposed model addresses these two important aspects of chain-wide and store-level cross-category analysis. First, our proposed factor-regression model takes store differences and longitudinal market shifts into account, thereby providing the retail chain manager with unbiased global, chain-level estimates. It also provides stable local estimates of cross-category promotion effects at the store level. Second, while allowing this flexibility, our proposed model is parsimonious enough over existing alternatives, making it particularly useful for chain-wide and store-level cross-category analysis.We apply the proposed model to store-level data from one retail chain, comparing it with several competing approaches, and demonstrate that it provides the best balance between flexibility and parsimony. Most importantly, we show that the proposed model provides useful insights regarding cross-category effects at the chain-level, for individual stores, and their patterns across stores.     

Big-box retailing and the urban retail structure: the case of the Toronto area

This paper examines the growth and impact of power centres and “big-box” retailers through the 1990s in the Greater Toronto Area (GTA). The data reveal that 72% of big boxes were added in the previous nine years and that twice as many opened in the suburban fringe as compared to the equally populated central area. Of all big-box locations, 59% are on industrial lands and close to expressways. Of all postal codes in the GTA, 11% account for 47% of the big-box locations and a 19% versus 7% of 1989–1995 sales growth. Average annual sales per store in the heavily dominated big-box areas is $2+million versus $1.4 million in non-box areas and market shares for the dominant big-box retailers range between 19 and 33% in their respective retail categories. In eight retail sectors in direct competition with big-box retailers, there is an overall decline of −7% in share of total stores. Between 1993 and 1997, the proportion of retail employment within 2 km of a big-box increased from 28 to 43%. This increase is accounted for by additional retail and service firms.     

Sales employees’ polychronicity and sales-service ambidexterity: Mediation of work engagement and moderation of store manager support

Sales employees are encountered with increasing job demands and volatile changes in the retail environment. In particular, the adoption of smart technologies in the retail sector has pressurized sales employees to be versatile and agile in the new marketplace. In this sense, performing multiple tasks within a limited time frame has become an important quality required for sales employees. Grounded in the job demands-resources model, we proposed that sales employees’ individualized resource (i.e., polychronicity) would be positively related to their sales-service ambidexterity though work engagement. We further posited that an organizational resource (i.e., store manager support) synergistically interacted with polychronicity to predict work engagement and subsequent sales–service ambidexterity. To test propositions, we collected multilevel data from 292 sales employees in 43 home-furnishing stores in India. Results demonstrated that the positive association among work engagement, polychronicity, and sales–service ambidexterity was more pronounced when store manager support was high than when it was low. These findings offer implications to overcome challenges faced by retail stores by indicating factors predicting sales–service ambidexterity in retail.     

Market and Product Diversification: The Evidence From Retailing

This study explored the number of international regions in which retailers operate, the assortment of product categories they offer their customers, and the effects of these market and product category diversification strategies on retail sales volumes. The analysis used sales data about 246 global large-scale retail stores from diverse industries and countries of origin. We found that both strategies have positive effects on retail sales volumes. The two strategies interact such that the positive effect of market expansion on retail sales volumes is larger for retailers who also follow a strategy of greater product category diversity.     

Open all hours: spatiotemporal fluctuations in U.K. grocery store sales and catchment area demand

Conventional population estimates do not account for spatiotemporal fluctuations in populations over a diurnal timescale at the level of retail store catchments. This presents challenges for the retail location-based decision making process which seeks to predict sales volumes and their temporal characteristics prior to new store construction. We present a novel analysis of the temporal fluctuations of store sales, evidencing links between the spatiotemporal distribution of specific population subgroups and temporal store sales. Previous research linking spatiotemporal populations and store sales is limited owing to the fact that commercial data are not openly available to academic research. However, this research has unprecedented access to store level temporal sales data and an established loyalty card scheme from a major UK grocery retailer making these analyses possible for the first time. Additionally, we demonstrate that current store classifications were inadequate for grouping stores with similar sales profiles and propose four new clusters of stores based on the times of the day that they generate revenues. This development has clear academic and commercial benefits, aiding our understanding of consumer behaviours and a novel solution for improved location modelling. We lay the foundations for further research building spatiotemporal demand fluctuations into retail location models.     

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.     

Interplays between manufacturer advertising and retailer store brand introduction: Agency vs. wholesale contracts

In retail supply chains, manufacturers' advertising for national brands and retailers' store brand introduction may relate to each other, and two types of contracts, i.e., agency contract and wholesale contract, are widely used. This paper uses game-theoretic models to investigate the strategic interaction between a manufacturer's advertising strategy and a retailer's store brand introduction strategy. We derive the equilibrium outcomes, including wholesale price, retail price, market demand, retailer's and manufacturer's profits under different contract forms. We find that when the product cost is small relative to the perceived value of the store brand, the introduction of a store brand will benefit the retailer. The retailer is more likely to introduce store brands under the wholesale contract than under the agency contract. In addition, compared with the wholesale contract, the agency contract may increase both the manufacturer's and the retailer's profits and lead to Pareto improvement for them.     

How storefront displays influence retail store image

The image of retail stores offers an important means for differentiation in highly competitive retail markets. Storefront displays generally function to increase attention to the store or generate unplanned store visits, whereas their impact on store image remains unknown. This study therefore investigates perceived image differences between commonly used types of storefront displays and tests whether an image transfer takes place from the display to the retail store. The results show that more innovative displays achieve better image valuations and that store image benefits from the presence of a storefront display. Spillover effects from the display to the store even occur in the face of some resistance, such as in familiar stores and among consumers who have negative attitudes toward such displays.     

The Magnitude of Change Effect in Store Remodeling

While store remodeling can increase customer sales, not all remodeling efforts are successful. In this study, two treatment stores from a large national retailer are matched with control stores in a field experiment. Even though the cost of remodeling the treatment stores was the same, and the remodeled stores had identical layout, color, furnishing and interior design, one store had a 12% lift in sales while the other had only 1%. We show that a key determinant of remodeling success is the perceived magnitude of change between the initial and final condition of the store. Indeed, customer psychological and sales responses are greater when the perceived magnitude of change between the condition of the store prior to remodeling and the store after remodeling is larger. Importantly, these positive effects continue for as long as 12 months after remodeling. We further find that the profile of customers drawn to the remodeled stores differs based on the perceived magnitude of change, as do the environmental attributes that contribute to customer perceptions of the remodel.     

Using workplace population statistics to understand retail store performance

We explore the value of recently released workplace geographies and accompanying census-based workplace zone statistics (WZS) and an associated classification of workplace zones (COWZ). We consider how these data could support retailers in their operational and strategic decision-making, including the evaluation of retail demand and retail store performance in localities where trade is driven by non-residential demand. In collaboration with major UK grocery retailer The Co-operative Group we explore the relationship between workplace population composition and store trading characteristics using a series of case study stores within Inner London. We use empirical store trading data to identify store and product category level temporal sales fluctuations attributable to workplace populations. We also use census-derived flow data to identify the spatial origins of workplace population inflow. We identify that store performance exhibits characteristics attributable to demand driven by these populations. We conclude that workplace population geographies, WZS and the COWZ afford considerable potential for understanding drivers of store performance, observed store trading patterns and evaluation of retail store performance. We suggest that the next step is to build these populations and their micro geography spatial and temporal characteristics into predictive models and evaluate their potential for store performance evaluation and location-based store and network decision-making within this sector.     

The Impacts of Retail Promotions on the Demand for Orange Juice: A Study of a Retail Chain

This study examined the impacts of retail promotions on the demand for five brands of orange juices for a retail chain (referred to as Retailer X) and its competitors using the Rotterdam model. Results show that the combination of feature ads and displays had the largest impacts on retail revenue among the four promotional tactics considered, whereas temporary price reductions had no advertising impacts on retail revenue. Results also show that when Retailer X promotes an orange juice (OJ) brand using any of the tactics, a larger portion of the increased demand for the promoted brand comes from reduced demand for other brands of OJ in the same store or chain.A smaller portion comes from the decreased demand in Retailer X's competing stores in the same trading area.     

Store and store format loyalty measures based on budget allocation

In highly competitive environments, such as retail markets, characterized by a growing heterogeneity of demand and the proliferation of new retail formats, cross-shopping behavior between stores and formats is becoming increasingly common. This process makes customer loyalty a key strategic challenge for retailers that want to consolidate their position within the market. To contribute to the analysis and comprehension of this reality, the authors propose and assess different objective indicators of store loyalty, store format loyalty, and intra-format store loyalty based on budget allocation. Specifically, they analyze the role of retail format in observable loyalty patterns in a market. Through an empirical analysis of grocery purchase patterns of a sample of 580 Spanish households, the authors find that diverse objective loyalty indicators based on budget allocations provide very similar information from a practical point of view. They also find that consumers' regular use of various formats (specifically, supermarkets, hypermarkets, and discount stores) for their purchases explain observed disloyalty better than does purchasing in several stores within these formats. The observed patterns reveal that retail formats define differentiated store profiles that relate to the benefits sought in different purchase situations.