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Optimal Business Location Model


The idea behind this paper is to create a model that will predict the optimal place for a business to locate. In order to ensure long run viability, a firm must understand the idea of optimal business location. In the designing of a strategy, it is important to not only evaluate the present market environment but to also account for possible future change. This paper will demonstrate the core ideas behind a comprehensive location model that will predict the optimal location for a business. The effectiveness of the model will be evaluated by using past data in Durham, North Carolina to predict current retail development and to see if the trend recognized would be able to correctly identify the location choices of firms. Further analysis will show what this foretells for Durham’s future retail locations.

The remainder of the paper can be found here.

A presentation on this topic can also be found here.

Bibliography:

1. Chi S.C., Kao S.S., Kuo R.J., “A decision support system for selecting convenience store location through integration of fuzzy AHP and artificial neural network.” Elsevier Science B.V., June 15, 2001.

2. Craig Samuel, Ghosh Avijit. “Formulating Retail Location Strategy in a Changing Environment.” The Journal of Marketing, Vol. 47, No. 3, 1983. pp 56-68.

3. Glaeser, Edward L., Rosenthal, Stuart S., Strange, William C., “Urban Economics and Entrepreneurship.” National Bureau of Economic Research. Working Paper 15536.

4. Huff, David L., “A Programmed Solution for Approximating an Optimum Retail Location.” Land Economics Vol. 42 No. 3, Aug. 1966. pp 293-303.


4 Comments

  1. Wow, very impressive. Clearly took a lot of work in matlab to produce these graphs.

    It is a little difficult to understand your presentation without your explanation, so I assume we will be able to understand all your graphs better on Wednesday. Just make sure to thoroughly explain your graphs, equations, and maps in the later slides so everyone in class can keep up.

    I also found it extremely interesting that the most successful locations in your model seem to follow 15-5o1, where I know a lot of currently well running businesses operate. From this, it looks like your model is a fairly good predictor of success.

    Slides looks good, presentation seems interesting, and I look forward to hearing it on Wednesday.

  2. This is an interesting analysis of a topic that is applicable to us all. I find particularly interesting your projection for the Hayti district.

    I am somewhat curious about the source of your data, and I don’t exactly understand how you derived your final optimal place values. This may be a point you wish to clarify in your paper and presentation,.

  3. A very interesting and impressive approach to modeling the optimal location problem that is able to appropriately quantify a wide range of factors. I liked how you added the analysis of consumers’ valuation of the cost of doing business through the physical distance from the firms, and the first derivatives.

    I was wondering if there was any probability of self reinforcing behavior/queen bee syndrome, in the sense that if a major firms happens to locate in an area, other firms may be drawn to that area due to not just the physical characteristics of the place (that you model) but the inherent consumer base that would be drawn to that area by the large firm.

    It would be interesting to see what types of firms cluster in each area as well, if they are homogenous or a heterogenous mix.

  4. This was a very interesting project.
    As you said, many different variables can be taken into consideration specially depending on the time of business. I would love to see your model being used for a big chain and how they would evaluate it. Do you also think McDonalds or other chain restaurants use models like yours to analyze where they are going to open their next shop?
    Great work.

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