Incorporating E‐commerce into Retail Location Models. Issue 2 (16th March 2021)

• Record Type: Journal Article
• Authors: Beckers, Joris; Birkin, Mark; Clarke, Graham; Hood, Nick; Newing, Andy; Urquhart, Ryan
• Is Part Of: Geographical analysis. Volume 54:Issue 2(2022)
• Page Start: 274
• Page End: 293
• Publication Date: 2021-03-16
• Subjects: Geography -- Methodology -- Periodicals; Electronic journals; 910.00182
• DOI: 10.1111/gean.12285
• Languages: English
• ISSNs: 0016-7363

Abstract

Abstract : The use of location models in retail businesses is well‐established, particularly in the grocery sector. Many alternative methods are in use today but the spatial interaction model (SIM) has a proven record of success. To date, that success relates purely to face‐to‐face activities, modeling and predicting visits by consumers to retail outlets. However, grocery retailers are cutting back on store investments and concentrating on investment in the convenience market and e‐commerce: the latter has now reached a 7.2% share of the U.K. grocery market, with continued growth forecast. Although spatial models are used extensively for helping to locate new convenience stores, so far e‐commerce has not been built into existing retail location models. Yet e‐commerce seems to be a spatial activity. Extensive evidence demonstrates the geography of demand and supply are as important in groceries e‐commerce as they are in face‐to‐face grocery retailing. We therefore take up the challenge of incorporating e‐commerce into classic location models. Methodologically, we find the standard distance deterrent term in the production‐constrained SIM unsuitable for modeling e‐commerce flows: we explore inverting this term and find extensive gains in prediction accuracy, an interesting finding that contributes to the ongoing applied SIM literature.