Buy online collect in-store: Exploring grocery click & collect using a national case study



Davies, AE ORCID: 0000-0002-4538-1375, Dolega, Les ORCID: 0000-0002-1340-6507 and Arribas-Bel, Dani
(2019) Buy online collect in-store: Exploring grocery click & collect using a national case study. International Journal of Retail & Distribution Management, 47 (3). 278 - 291.

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Abstract

21st century online retailing has reshaped the retail landscape. Grocery shopping is emerging as the next fastest growing category in online retailing in the UK, having implications for the channels we use to purchase goods. Using Sainsbury’s data, we create a bespoke set of grocery click&collect catchments. The resultant catchments allow an investigation of performance within the emerging channel of grocery click&collect. The spatial interaction method of ‘Huff gravity modeling’ is applied in a semi-automated approach, used to calculate grocery click&collect catchments for 95 Sainsbury’s stores in England. The catchments allow investigation of the spatial variation and particularly rural-urban differences. Store and catchment characteristics are extracted and explored using ordinary least squares regression applied to investigate ‘demand per day’ (a confidentiality transformed revenue value) as a function of competition, performance and geodemographic factors. Our findings show that rural stores exhibit a larger catchment extent for grocery click&collect when compared with urban stores. Linear regression finds store characteristics as having the greatest impact on demand per day, adhering to wider retail competition literature. Conclusions display a need for further investigation (e.g. quantifying loyalty). New insights are contributed at a national level for grocery click&collect, as well as e-commerce, multichannel shopping and retail geography. Areas for further investigation are identified, particularly quantitatively capturing brand loyalty. The research has commercial impact as the catchments are being applied by Sainsbury’s to decide the next 100 stores and plan for the next five years of their grocery click&collect offering.

Item Type: Article
Uncontrolled Keywords: Linear regression, Retail patronage,, Click&collect, Retail catchments, Retail geography, Spatial interaction modelling
Depositing User: Symplectic Admin
Date Deposited: 04 Feb 2019 12:13
Last Modified: 17 May 2022 07:11
DOI: 10.1108/IJRDM-01-2018-0025
Open Access URL: https://doi.org/10.1108/IJRDM-01-2018-0025
URI: https://livrepository.liverpool.ac.uk/id/eprint/3032241