Abstract
Purpose The purpose of this paper is to study the optimization of the geographical location of a network of points of sale, so that each retailer can have access to a potential geographic market. In addition, the authors study the importance of the distance variable in the commercial viability of a point of sale and a network of points of sale, analysing if the best location for each point (local optimum) is always the best location for the whole (global optimum). Design/methodology/approach Location-allocation models are applied using p-median algorithms and spatial competition maximization to analyse the actual journeys of 64,740 car buyers in 1240 postal codes using a geographic information system (GIS) and geomarketing techniques. Findings The models show that the pursuit of individual objectives by each concessionaire over the collective provides poorer results for the whole network of points of sale when compared to coordinated competition. The solutions provided by the models considering geographic and marketing criteria permit a reduction in the length of journeys made by the buyers. GIS allows the optimal control of market demand coverage through the collaborative strategies of the supplying retailers, in this case, car dealerships. Originality/value The paper contributes to the joint research of geography and marketing from a theoretical and practical point of view. The main contribution is the use of information on actual buyer journeys for the optimal location of a network of points of sale. This research also contributes to the analysis of the correlation between the optimum local and optimum global locations of a commercial network and is a pioneering work in the application of these models to the automotive sector in the territorial area of the study.
Highlights
There is increasing interest in the potential opportunities arising from extracting spatial information from large data sets (Comber et al, 2016)
The application of the reduction models allows, at each stage, the progressive elimination of the locations with less influence on the market share of the network ( Jong de and Tilema, 2005; Breukelman et al, 2009). Given that both the market volume and the location of the dealerships are relevant variables, the algorithm of average distance travelled by customers ( p-median) and the algorithm of elimination of locations with poor results are applied through the reduction model depending on the volume of registrations
4.1 Selection of the eleven dealerships To begin the process of deciding the best solution among the proposals, a comparison must be made between the solutions of the average distance algorithms and the maximization of the individual quota
Summary
There is increasing interest in the potential opportunities arising from extracting spatial information from large data sets (Comber et al, 2016). A geographic information system (GIS) is needed: “a computer application capable of creating, storing, manipulating, visualizing and analysing geographic information” GISs are widely applied in developed countries, such as the USA or Great Britain (Allo, 2014). Their widespread use has made them a tool for sharing and communicating knowledge about the earth’s surface (Sui and Goodchild, 2011). There is an increasing interest in visualizing and analysing spatio-temporal data through geo-intelligence tools (Bozkaya and Singh, 2015; Altshuler et al, 2015; Lucas et al, 2015)
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