Skip to main content

Industrial Location Modeling: Extending the Random Utility Framework

Buy Article:

$43.00 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.
No References
No Citations
No Supplementary Data
No Data/Media
No Metrics

Document Type: Research Article

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

Publication date: 2004-02-01

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed 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