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.</p

The impact of hard discounter presence on store satisfaction and store loyalty

Hard discounters, such as Aldi and Lidl, have become more important in the last decade. Recent research suggests that the presence of a hard discounter (HD) decreases customers' share of wallet. In this study, we aim to understand why this occurs, by considering how HD presence affects store attributes and store satisfaction. In particular, we investigate whether HD presence affects store satisfaction formation as well as the effect of store satisfaction on share of wallet. We analyze Dutch data on store attribute evaluations, store satisfaction and share of wallet. Our results show that HD presence decreases convenience evaluations of a store, satisfaction and share of wallet. Moreover, we show that the relationship between convenience and store satisfaction becomes more important when a HD is present, while we then also find a stronger positive relationship between satisfaction and share of wallet. Simulations based on our model estimations show that especially price-oriented retailers should fear decreases in share of wallet when a HD is present

Å estimere handelsområder uten å følge kundene hjem

Det er svært viktig å forstå den geografiske utstrekningen for varehandelsområder i detaljhandel. Gjeldende metoder for å tegne opp varehandelsområder er basert på undersøkelser og data fra lojalitetskort. Disse tilnærmingene bruker kundedata på husholdningsnivå til å koble postnummer sammen med butikker, og dette har flere ulemper: unøyaktighet i undersøkelser, ikke-representative data, kostbar datainnsamling og/eller data som kun gjelder butikker innenfor egne kjeder uten at andre kjeder tas med i betraktningen. Vi har utviklet en ny metode for å skissere opp handelsområder. Datakravene er at man må kjenne til de samlede salgsinntektene for butikker, butikkenes egenskaper, populasjonens egenskaper på postnummer-nivå, og avstander mellom butikker og postnummer. Denne typen data er enten offentlig tilgjengelig eller samles vanligvis inn av dataanalyseselskaper som AC Nielsen og Experian, og de er dermed lette å få tak i. Vår tilnærming kan gi handelsområdet til enhver butikk som tilhører enhver kjede, er basert på objektive data og krever ikke kundedata på husholdningsnivå for å koble postnummer til butikker. Isteden forsøker vi å hente ut kundekrets basert på postnummer ved å bryte ned butikkenes samlede salgsnivåer til komponenter som kan tilskrives postnumrene der husholdningene holder til. Vi illustrerer potensialet til den nye modellen med et datasett fra Experian som inneholder alle dagligvareforretninger i Oslo, samt populasjonens egenskaper og reiseavstander på grunnkrets-nivå

Advances in methods to support store location and design decisions

[Nog geen abstract]

The Impact of Hard Discounter Presence on Store Satisfaction and Store Loyalty

Hard discounters, such as Aldi and Lidl, have become more important in the last decade. Recent research suggests that the presence of a hard discounter (HD) decreases customers’ share of wallet. In this study, we aim to understand why this occurs, by considering how HD presence affects store attributes and store satisfaction. In particular, we investigate whether HD presence affects store satisfaction formation as well as the effect of store satisfaction on share of wallet. We analyze Dutch data on store attribute evaluations, store satisfaction and share of wallet. Our results show that HD presence decreases convenience evaluations of a store, satisfaction and share of wallet. Moreover, we show that the relationship between convenience and store satisfaction becomes more important when a HD is present, while we then also find a stronger positive relationship between satisfaction and share of wallet. Simulations based on our model estimations show that especially price-oriented retailers should fear decreases in share of wallet when a HD is present

Store sales evaluation and prediction using spatial panel data models of sales components

This paper sets out a general framework for store sales evaluation and prediction. The sales of a retail chain with multiple stores are first decomposed into five components, and then each component is explained by store, competitor and consumer characteristics using random effects models for components observable at the store level and spatial error random effects models for components observable at the zip code level. We use spatial panel data over four years for estimation and a subsequent year for evaluating one-year-ahead predictions. Set against a benchmark model that explains total sales directly, the prediction error of our framework is reduced by 34% for existing stores during the sample period, by 5% for existing stores one year ahead and by 26% for new stores.publishedVersio

The moderating role of shopping trip type in store satisfaction formation

Consumers may weigh store attributes differently depending on the type of shopping trip. For example, fill-in shoppers likely value convenience, due to the ad-hoc nature and urgency of such trips. However, no study has yet explored the effects of shopping trip types on satisfaction formation. This study investigates how three types of shopping trips — major, regular fill-in, and special fill-in — affect satisfaction formation. Using data for all Dutch grocery chains from 2009–2014, we show that service, price, and convenience are important drivers of satisfaction. We also find that the effects of these drivers on store satisfaction depend on the shopping trip type. Major shoppers, for instance, treat service factors as less important to their satisfaction than other shoppers do. Convenience is a more important driver of satisfaction for regular fill-in shoppers. Price is a more important determinant of satisfaction on fill-in trips related to special occasions like birthdays and family dinners