Defining and Estimating a Trading Area

Huff, David L.

doi:10.1177/002224296402800307

Cited by 757 publications

(428 citation statements)

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“…Following Huff (1964), we consider that the patronizing behavior of customers is probabilistic, that is, demand points split their buying power among the facilities proportionally to the attraction they feel for them. The attraction that a demand point feels for a facility depends on both the location of the facility and its quality (as perceived by the demand point).…”

Section: A Planar Competitive Location and Design Model And A Weiszfementioning

confidence: 99%

A robust and efficient algorithm for planar competitive location problems

et al. 2007

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In this paper we empirically analyze several algorithms for solving a Huff-like competitive location and design model for profit maximization in the plane. In particular, an exact interval branch-and-bound method and a multistart heuristic already proposed in the literature are compared with UEGO (Universal Evolutionary Global Optimizer), a recent evolutionary algorithm. Both the multistart heuristic and UEGO use a Weiszfeld-like algorithm as local search procedure. The computational study shows that UEGO is superior to the multistart heuristic, and that by properly fine-tuning its parameters it usually (in the computational study, always) find the global optimal solution, and this in much less time than the interval branch-and-bound method. Furthermore, UEGO can solve much larger problems than the interval method.

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Section: A Planar Competitive Location and Design Model And A Weiszfementioning

confidence: 99%

A robust and efficient algorithm for planar competitive location problems

et al. 2007

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“…There are two main branches in competitive facility location depending on the assumptions about consumer behavior. One applies the gravity model suggested by Reilly (1931) and applied to a retail competitive environment by Huff (1964), Huff (1966). Locating a facility by this model was first introduced by Drezner (1994b).…”

Section: Literature Reviewmentioning

confidence: 99%

“…If distances are almost the same, the votes are divided more evenly among the competitors. Such an approach is similar to the gravity model in competitive facility location (Reilly 1931;Huff 1964Huff , 1966Drezner 1994a). …”

Section: Literature Reviewmentioning

confidence: 99%

The wisdom of voters: evaluating the Weber objective in the plane at the Condorcet solution

Drezner

Menezes

2015

Ann Oper Res

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We investigate the quality of Condorcet solutions when compared to a central decision maker solution in the context of a facility location model in the plane. We perform an extensive set of experiments and conclude that if each population member votes according to his/her own self interest, then the Weber objective at the Condorcet solution point is very close to the optimal Weber objective value. Reducing the set of voters has little impact on the quality of the Condorcet solution. Being short of a good candidate has some impact but the final decision is still a good one. The distance metric seems to be of little relevance as well. As long as candidates are diverse, the Condorcet solution results in a good decision when compared to the decision by a benevolent dictator.

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“…We explore the modeling rationale for the location decision and analyze the implications for location. We analyze the model using the gravity model (Reilly 1931;Converse 1949) introduced to retail location by Huff (1964Huff ( , 1966 and later extended by Nakanishi and Cooper (1974). Huff used the floor area as a surrogate for attractiveness.…”

Section: Problem Statementmentioning

confidence: 99%

Location of retail facilities under conditions of uncertainty

Drezner

2007

Ann Oper Res

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Models for the optimal location of retail facilities are typically premised on current market conditions. In this paper we incorporate future market conditions into the model for the location of a retail facility. Future market conditions are analyzed as a set of possible scenarios. We analyze the problem of finding the best location for a new retail facility such that the market share captured at that location is as close to the maximum as possible regardless of the future scenario. The objective is the minimax regret which is widely used in decision analysis. To illustrate the models an example problem is analyzed and solved in detail.

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Defining and Estimating a Trading Area

Abstract: What are the conceptual properties of a trading area? What is the definition of the term? What testable propositions are currently available to validate its properties and thus give precision to the definition? This article gives answers to these questions.

Cited by 757 publications

References 0 publications

A robust and efficient algorithm for planar competitive location problems

A robust and efficient algorithm for planar competitive location problems

The wisdom of voters: evaluating the Weber objective in the plane at the Condorcet solution

Location of retail facilities under conditions of uncertainty

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