Skip to main content

Industrial Location Modeling: Extending the Random Utility Framework

Buy Article:

$51.00 plus tax (Refund Policy)



Given sound theoretical underpinnings, the random utility maximization‐based conditional logit model (CLM) serves as the principal method for applied research on industrial location decisions. Studies that implement this methodology, however, confront several problems, notably the disadvantages of the underlying Independence of Irrelevant Alternatives (IIA) assumption. This paper shows that by taking advantage of an equivalent relation between the CLM and Poisson regression likelihood functions one can more effectively control for the potential IIA violation in complex choice scenarios where the decision maker confronts a large number of narrowly defined spatial alternatives. As demonstrated here our approach to the IIA problem is compliant with the random utility (profit) maximization framework.

Document Type: Research Article


Affiliations: 1: Universidade do Minho and CEMPRE, 4710-057 Braga, Portugal. 2: Universidade do Porto and CEMPRE, 4200-464 Porto, Portugal. 3: 3University of South Carolina, Columbia, SC 29208.

Publication date: February 1, 2004


Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more