Business opportunities analysis using GIS: the retail distribution sector

Abstract

The retail distribution sector is facing a difficult time as the current landscape is characterized by ever-increasing competition. In these conditions, the search for an appropriate location strategy has the potential to become a differentiating and competitive factor. Although, in theory, an increasing level of importance is placed on geography because of its key role in understanding the success of a business, this is not the case in practice. For this reason, the process outlined in this paper has been specifically developed to detect new business locations. The methodology consists of a range of analyzes with Geographical Information Systems (GISs) from a marketing point of view. This new approach is called geomarketing. First, geodemand and geocompetition are located on two separate digital maps using spatial and non-spatial databases. Second, a third map is obtained by matching this information with the demand not dealt with properly by the current commercial offer. Third, the Kernel density allows users to visualize results, thus facilitating decision-making by managers, regardless of their professional background. The advantage of this methodology is the capacity of GIS to handle large amounts of information, both spatial and non-spatial. A practical application is performed in Murcia (Spain) with 100 supermarkets and data at a city block level, which is the highest possible level of detail. This detection process can be used in any commercial distribution company, so it can be generalized and considered a global solution for retailers.

Using Twitter to explore consumers' sentiments and their social representations towards new food trends

“…Kernel density is a Twitter, consumers and new food trends non-parametric method used to estimate the intensity of points by calculating a smooth surface based on a bivariate normal probability distribution (Bailey and Gatrell, 1995). This approach has been extensively used to explore spatial patterns in consumer behaviour and Twitter's sentiment analysis (Roig-Tierno et al, 2013;Widener and Li, 2014).…”

Food and non-food retail change in a post-communist country:A case study of the Gemer region in Slovakia

“…GIS is often considered an appropriate tool to handle the issue of retail unit location (see Birkin et al, 1996;Roig-Tierno et al, 2013;Murad, 2014). In the article, two basic techniques were applied: location analysis and variable attribute analysis (Goodchild et al, 1992).…”

Assessing food retail competitors with a multi-criteria GIS-based method

“…We analysed 12,382 city blocks. This procedure is called geodemand and can be defined as digitally mapping the customers of a product or service in a particular market (Roig-Tierno et al, 2013b). Table 4 shows the results of this analysis: CI (m), size or sales floor area (m 2 ), sales (€), sales per m 2 (€/m 2 ), population in the trade area (supermarket's potential market) and the average spend per person (€/person).…”