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.     

Estimating small-area demand of urban tourist for groceries: The case of Greater London

Tourist retail demand within urban areas brings both opportunities and challenges to the local economy. Taking Greater London as the study area, this paper integrates conventional statistics and survey datasets with novel crowdsourcing big data sources to identify and estimate four types of tourist grocery demand at the small-area scale: travellers staying with Airbnb, tourists using traditional commercial accommodation, guests staying with relatives or friends and day trip visitors. Based on this combined tourist retail demand layer we show the spatial variations at the small-area level and as an illustration of the demand uplift, we estimate additional grocery expenditure that is associated with this tourist demand. Thus, the paper indicates the neighbourhoods with significant grocery demand uplift from tourist stays. We argue that the new retail demand layer has tremendous potential to be used as an additional input to retail location modelling tools to support new store revenue estimation and store performance evaluation within the grocery retail sector.     

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.     

The Implications of Mismatching Organizational Decision-making and Communication Structures within US Retail Firms: the Role of Scanner Data

Scanner data processed in an efficient manner can provide retail organizations with a powerful managerial tool that can be used to support corporate buyers' merchandising decisions, manage inventory, provide retail sales support, and evaluate individual store performance. In the light of such potential, we examine how the distribution of scanner-generated information interacts with the locus of decision-making authority and affects the relationship between corporate buyers and store managers. We suggest that to avoid potential intra-firm conflicts between the corporate and store levels, the communication structure within an organization should be matched with a decision-making structure that shares a similar level of decentralization.     

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.     

Effects of neighbourhood characteristics on store performance supermarkets versus hypermarkets

We investigate the impact of neighbourhood characteristics on the relative attractiveness of product categories within a store, with special attention for the differences between hypermarkets and supermarkets. We consider two questions. Firstly, is the impact of neighbourhood-specific factors on attractiveness of product categories smaller for hypermarkets than for supermarkets? Secondly, is there a difference in relative attractiveness of product categories between supermarkets and hypermarkets and to what extent is this difference dependent on kind of neighbourhood? For the impact of store and trading area characteristics on category and store performance, we use a framework that was originally presented in Campo et al. (J. Int. Res. Market 17 (2000) 225). Empirical application to national stores of a European retail chain confirms the differential impact of neighbourhood characteristics on supermarkets and hypermarkets. The research proves that geomarketing analysis can be useful for developing micromarketing strategies.     

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.     

Evaluating the potential of agent-based modelling to capture consumer grocery retail store choice behaviours

Evolving consumer behaviours with regards to store and channel choice, shopping frequency, shopping mission and spending heighten the need for robust spatial modelling tools for use within retail analytics. In this paper, we report on collaboration with a major UK grocery retailer to assess the feasibility of modelling consumer store choice behaviours at the level of the individual consumer. We benefit from very rare access to our collaborating retailers’ customer data which we use to develop a proof-of-concept agent-based model (ABM). Utilising our collaborating retailers’ loyalty card database, we extract key consumer behaviours in relation to shopping frequency, mission, store choice and spending. We build these observed behaviours into our ABM, based on a simplified urban environment, calibrated and validated against observed consumer data. Our ABM is able to capture key spatiotemporal drivers of consumer store choice behaviour at the individual level. Our findings could afford new opportunities for spatial modelling within the retail sector, enabling the complexity of consumer behaviours to be captured and simulated within a novel modelling framework. We reflect on further model development required for use in a commercial context for location-based decision-making.     

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。     

The Role of Customer Factors in Multiple Store Patronage: A Cost-Benefit Approach

This paper is concerned with the use of multiple stores by supermarket customers. It relates the number of stores patronized to a set of customer factors under a unifying theoretical framework emphasizing cost-benefit analysis. Respective hypotheses are tested in a large random sample. This study is a first attempt to empirically address the structure of multiple store patronage. It is demonstrated that multiple store patronage is affected by variables such as customer income, satisfaction, and expenditure that are suggestive of heterogeneous cost-benefit tradeoffs and opportunity costs of time. It is shown that customers are intrinsically different in the predisposition to being loyal. In this respect, store patronage is a continuum between single store loyalty and use of several different stores, on which customers vary depending on individual preferences. The empirical analysis also suggests that exclusive patronage of the favorite store arises from two observationally equivalent latent segments that differ in their inclination to remain loyal. The results yield valuable insights into the structure of store patronage and lead to important implications for retail managers. Several extensions are considered. A broad set of research questions surrounding store patronage can be considered from a cost-benefit viewpoint in the sense that consumer decisions in this area involve trading off economic resources against assortment, spatial and temporal benefits.     

Retailing as a career: a comparative study of marketers

This note reports how positions in retailing—particularly store-based positions—compare with other marketing-related positions. While much of the past literature concerning work experiences in retail settings is primarily perceptual and anecdotal, the results of this nationwide study are based on an examination of actual workplace experiences in marketing-related positions. The findings suggest that workplace experiences in corporate retailing are positive and equivalent to other marketing-related careers. However, workplace experiences in retail store management are less satisfying. The retail store managers studied were paid less, experienced less variety and autonomy on the job, felt less satisfied and committed to their work, and had greater turnover intentions compared to the other marketing managers studied. Managerial implications and recommendations are presented.     

Assessment of business potential at retail sites: empirical findings from a US supermarket chain

We address the problem of estimating retail business potential at alternative sites, with concern for assessing performance relative to potential in existing markets and for identifying the best sites for expansion into new markets. At question is the utility of information typically used in formal retail patronage models, in comparison with additional information considered important by retail executives. Relevant data are gathered from secondary sources and intensive in-store surveys are conducted to produce a portfolio of information about neighbourhood demographics, store ambience, variety and quality of products and services, relative prices of selected products, etc. for stores in a retail grocery chain and competitive stores in the chain's markets. We experiment with alternative statistical models for store performance to determine the consequence of restricting the types of data available when constructing the models. Our findings suggest that while information about store location and surrounding areas, store characteristics and competitive position are all required to obtain the best assessment for business potential at a site, a few key variables on each dimension offer the bulk of explanatory power. Further, the spatial-locational variables affect all measures of store performance in intuitive directions, whereas the effects of other variables differ according to performance measure and reflect the store's market position.     

零售业数字化转型机理研究

在数字经济时代,数字化转型已成为零售业高质量发展的必然趋势。近年来,我国零售企业纷纷进行数字化转型,呈现出从技术应用向数字赋能转变、从渠道线上化向线上线下一体化转变、从业务数据化向数据业务化转变、从营销数字化向全面数字化转变以及从大企业主导向大中小企业协同转变的特征,整体上处于探索阶段,存在着全面数字化战略规划缺失、数字化基础和能力较弱、需求驱动型供应链支撑不足和企业组织架构改革相对滞后等问题。零售业数字化转型的内在机理是数字化技术驱动的以消费需求为核心的生产供给体系和流通供给体系的变革,即以消费者需求为出发点,通过线上线下多维立体场景打造、供应链逆向整合、数据资源积累和数据分析能力构建、业务流程再造与组织架构变革构建数字化商业生态系统,打破商品生产与消费之间的时间与空间限制,重构人货场的关系,提升生产与流通体系供给质量和供给效率。     

Constructive deviance as a driver for performance in retail

A growing body of research is concerned with deviance in the workplace. While much research has explored negative forms of deviance, we examine constructive deviance: behaviour that deviates from salient norms and benefits the reference group. We empirically explore manifestations, determinants and performance outcomes of constructive deviance in standardised work processes. We do this through a mixed-methods study in bakery trading departments of an Australian retailer. We illustrate that constructive deviance occurs in these settings and show that some manifestations of constructive deviance improve organisational performance and pave the way for applying constructive deviance as a strategic tool in retail.     

Enhancing retail location decision support: The development and application of geovisualization

Geovisualization refers to the visual exploration, analysis, synthesis and presentation of geospatial data. This paper presents findings from research that has focused on developing and applying geovisualization techniques and technologies for use within retail location decision support. To date, retailers represent a major user group of geographic information system (GIS) -based decision support technologies, with applications ranging from trade area mapping to store portfolio planning. However, the ability to handle spatial–temporal data, visualize change, and explore the temporal dimension of spatial data is limited within conventional GIS. The paper details the development of a prototype geovisualization system that has been designed to enable visualization of spatial–temporal change of retail-related data. From this explicitly visual paradigm, a number of examples of potential analysis are examined at four different scales of analysis: national, regional, market and micro-level. The paper highlights both the challenges and potential to enhance retail decision support by integrating geovisualization techniques and technology within decision support activities.     

Black out of the blue light: An analysis of Kmart store closing decisions

We investigate the spatial and economic factors that influenced Kmart's decision to close about 600 under-performing stores as part of its Chapter 11 financial objectives review in 2002 and 2003. We develop a theoretical model of retail store location and estimate an empirical counterpart using a Logit model to investigate the economic and spatial factors that influenced this decision, including the degree and proximity of competition in the local market as well as local demographic characteristics. In general, our empirical results offer statistical support for the accepted paradigm, but our model offers modest predictive ability as to which stores were actually closed. One interesting extension is a discussion of the potential implications of store closing on the local population, especially with respect to low-income households’ access to discount stores.     

The Relationships Among Manager-, Employee-, and Customer-Company Identification: Implications For Retail Store Financial Performance

Based on the premise of an interpersonal “chain of influence” with respect to organizational identification, we posit a relationship between company managers, employees, and customers with respect to organizational identification with the retailer. Specifically, we hypothesize that the level of a store manager's identification with the retailer is positively related to the level of their store employees’ identification with the retailer, which in turn is positively related to the level of customers’ identification with the retailer, which results in increased levels of store financial performance. We investigate these relationships using data from 306 retail stores within a single retail chain.     

Retail network spatial expansion: An application of the percolation theory to hard discounters

This article concerns the spatial organization of a retail network. During the expansion of a retail network, the location decision process does not necessarily lead to a regular distribution of outlets throughout the territory. The case of 5 hard discount store networks in France in their development stage illustrates this situation. A hard discount network strategy to fight against incumbent stores relies on the postulate that its competitiveness stems from its perfect cost control, and consequently, its ability to impose its brands to the consumers. To explain hard discounter spatial strategies, the diffusion theory was primarily developed by retaining only the temporal dimension of the process. But this model is not well established for the disordered environment in which the networks are managed. The percolation theory facilitates a new approach of the diffusion in this disordered medium that represents the retail network.     

Customer satisfaction and retail sales performance: an empirical investigation

We measure the links between store attribute perceptions and customer satisfaction, and between customer satisfaction and sales performance. Our data set consists of six waves of customer satisfaction and sales data for about 250 retail outlets over the period 1998-2001 for a publicly held supermarket company. We construct a statistical model to address nonlinearities and asymmetries in the satisfaction-sales performance links, and we illustrate how retailers can affect store revenues by managing customer satisfaction. Contributions of our study include the analysis of behavioral consequences of customer satisfaction in the food retail sector, the accommodation of complexities in the satisfaction-sales performance links based on an empirical model of first differences, and a discussion of how managers can employ the results for customer satisfaction policies.