Convenience store location planning and forecasting – a practical research agenda

Abstract

Purpose: To compare the accepted techniques of location analysis in the food sector with the realities of "real world" forecasting in convenience store (c-store) retailing. To offer a conceptual framework for c-store operators intending to become more strategic in their small store location planning but currently lacking established expertise or extensive research budgets. Approach/Methodology: Outlines potential best practice based on industry experience, and contact and discussion with location analysts and retail consultants, as well as a wide ranging examination of the academic literature in this area. Research/practical implications: First, to briefly detail the strategic regulatory motivations and location planning implications of the major UK food retailers entering this market. Second, to summarise the established sales forecasting techniques in food retailing. Third, to review why these established approaches are difficult to apply to convenience stores in neighbourhood markets. Fourth, to detail basic approaches that should be further developed by small store operators lacking budgets to develop specialist location planning departments. Originality/value: Academic conceptualisations of location planning in the convenience store sector are largely absent from the literature. This paper adopts a practical perspective. Conceptual Paper

Location decision making in retail firms: evolution and challenge

“…The authors devised a typology that distinguished between "shopping mission" (convenience versus comparison) and a continuum of product "size" (in terms of its bulkiness or portability) to identify specific drivers of store performance. They argued that understanding the different drivers of trade between different retail business and types of location was becoming increasingly important for retailers attempting to understand the characteristics of their portfolio: The importance of making sense of micro-scale issues in location decision-making was further examined in a recent paper by Wood and Browne (2007) who -by focusing on convenience store sales forecasting -found that accurate data was often not available at this spatial scale of development and that the accepted models of forecasting were often not as applicable. Instead, they observed a relative increase in importance of the site visit at the expense of office-based analysis to identify the crucial factors not identified in conventional and established models but relevant to such formats.…”

Using workplace population statistics to understand retail store performance

“…Given the important role of workplace populations in driving trade at these city centre stores, we argue that the next step is to build these workplace populations into the spatial decision making tools used by retailers for site evaluation. Wood and Browne (2007) assert that location planning and analysis tools used for large food store development are 233) approach. Thus site visits and analogue approaches (predicting sales at proposed store investments by comparison with existing stores which are similar in size, location and catchment) remain important tools for convenience store location-based decision making (Birkin, Clarke, and Clarke 2016;Wood and Browne 2007) .…”

“…Wood and Browne (2007) assert that location planning and analysis tools used for large food store development are 233) approach. Thus site visits and analogue approaches (predicting sales at proposed store investments by comparison with existing stores which are similar in size, location and catchment) remain important tools for convenience store location-based decision making (Birkin, Clarke, and Clarke 2016;Wood and Browne 2007) . Within densely populated urban areas such analogies would commonly include footfall, visibility, local competition and adjacencies (complementary and competing services within the immediate store vicinity).…”

“…For large format store development retailers use sophisticated gravity or spatial interaction models (SIMs) and associated spatial decision support systems (SDSS) to predict interactions between retail demand and supply (accounting for store accessibility and attractiveness), enabling prediction of store revenues, retailer market shares and impacts of new store openings on competitors (Birkin, Clarke, and Clarke 2016;Wood and Browne 2007). Whilst we are unaware of current SIM applications for convenience store location-based decision making, ongoing research outlined by Hood, Clarke, and Clarke (2015) recognises the need to evaluate the potential contribution that spatial modelling, including the SIM, could make within the convenience foodstore sector.…”

Managing communities and managing knowledge: strategic decision making and store network investment within retail multinationals

“…Moutinho et al, 1993;Wood and Browne, 2007). In a practical sense this results in commercially available data sets and modelling techniques which are insufficiently tailored to either the spatial scale or locality under investigation.…”