Business GIS for Everyone

This blog takes an informal look into the debates and methods related to business GIS and mapping

Perspectives on Identifying Sound Business Locations: Part Three

Author: Dr. Murray Rice

This is the third of three posts that explore the perspectives that retail geographers have developed on how to identify the best locations for a business. The previous two posts have provided some background on this quest for application, and outlined the basics of four different analytical approaches to the problem. This third post discusses one final approach: location-allocation modelling.

Location-Allocation Modelling

Location allocation modelling is the wildcard in the set of five location approaches discussed in these three posts. The first four site selection frameworks of all involved some level of knowledge of the business and its peak markets. It would be unfair to characterize location allocation modelling as ignoring the details of the business and its markets, but it would be useful to say that this fifth framework conceptualizes the problem of site selection are in a new and unique way.

Location allocation modelling focuses on use of models that directly determine both optimal facility locations and the boundaries of the service zones associated with the entire set of business facilities. This is a powerful location modelling environment. Service zone definition has been largely ignored in the previous four models, even though service zones have an important role to play in the location problem. So this enhanced consideration of an important site factor is welcome. However, application of location-allocation comes with both strengths and weaknesses. Most prominently it would be fair to say that location allocation modelling is most applicable when the business has an entire regional network of facilities to locate in a short time, rather than a smaller number of incremental facility additions.

For example, say a retail chain with no history of operation in a given region decides to enter the region with a massive network of stores that collectively cover every market in the region (Figure 1). This is such a massive problem that implementing any of the first four location approaches would be difficult. There simply is a huge challenge in designing a network of this size and complexity. What is needed in this situation is an approach that emphasizes an optimal regional presence with the collective network of facilities, as opposed to identifying individually good locations.

Figure 1: Sample Location-Allocation Problem

The three principal approaches to location allocation modelling recognize that there are different but equally valid ways of defining an efficient network, depending on the business and the markets that it serves. The following define the basics of each of these three approaches. In considering these three approaches, it is important to understand that in many circumstances there is one approach that fits the needs of the business and its customers best.

• The P median approach to this problem.

• The maximal covering location approach

• The set covering location approach

Using Location-Allocation Methodologies in Maptitude

Location-allocation methods are one great way to see the amount of development that has gone into Maptitude in the last decade. While Maptitude has always been a great GIS for providing insight into individual facility location decisions, in the late 2010s Maptitude built a new Facility Location tool. and its substantial abilities to support the location of any number of facilities to serve a regional market.

Maptitude 2024 includes all three location allocation approaches defined here, although the terminology used in this post (which follows the terminology used in the research literature in this field) differs from Maptitude’s plain-English descriptions of the analytical options available. The following is a brief guide to Maptitude's facility location terminology in comparison to the terminology from the location-allocation literature.

Under "type of facility location" (see Figure 2),

• "Best overall service" refers to solution of both the p-median problem and the set covering problem (use of the set covering option requires you to define a coverage standard later)
• "Best service for clients farthest away" refers to the maximal covering problem
• "Keep faciIities away from clients" covers the novel situation of locating something like a landfill or a fire station that no client would want to be near (or at least immediately adjacent to). This is a powerful and useful objective that is included in Maptitude mapping software’s capabilities, but it is not one of the primary location-allocation approaches we explore here. It might be best thought of as a creative and useful methodology to have access to, but in comparison with the three foundational approaches, it is less likely to be used.

In all, the facility location tool in Maptitude provides several facility location analysis options that make it possible to solve complex location-allocation problems. Together with the options described in the last two posts, businesses can combine location-allocation with several alternative facility location options that respond well to the needs of a wide range of businesses.

Figure 2: Facility Location Options Provided by Maptitude