Building Spatial Choice Models from Aggregate Data

2003 ◽  
Vol 43 (2) ◽  
pp. 319-348 ◽  
Author(s):  
Tommi Orpana ◽  
Jouko Lampinen
Keyword(s):  
Choice Models ◽  
Aggregate Data ◽  
Spatial Choice

Dynamic e-targeting using learning spatial choice models

2006 ◽  
Vol 20 (3-4) ◽  
pp. 30-42 ◽  
Author(s):  
Wolfgang Jank ◽  
P.K. Kannan
Keyword(s):  
Choice Models ◽  
Spatial Choice

scholarly journals Bayesian estimation of random-coefficients choice models using aggregate data

2009 ◽  
Vol 24 (3) ◽  
pp. 490-516 ◽  
Author(s):  
Andrés Musalem ◽  
Eric T. Bradlow ◽  
Jagmohan S. Raju
Keyword(s):  
Bayesian Estimation ◽  
Choice Models ◽  
Aggregate Data ◽  
Random Coefficients

Hierarchical Elimination and Regionalization in Spatial Choice

1982 ◽  
Vol 14 (1) ◽  
pp. 127-130
Author(s):  
P B Slater
Keyword(s):  
Spatial Interaction ◽  
Choice Models ◽  
Tree Structure ◽  
Choice Probability ◽  
Ratio Model ◽  
Flow Data ◽  
Constant Ratio ◽  
Spatial Choice ◽  
Natural Explanation ◽  
Elimination By Aspects

Spatial choice models have been criticized for their restrictive assumptions. In particular, the independence or constant-ratio axiom of Luce has been questioned because of its failure to account for the effects of similarity between alternatives. Tversky's elimination by aspects model provides a natural explanation of similarity effects, but cannot be estimated from binary probabilities. The elimination by tree or, equivalently, hierarchical elimination model is less restrictive than the constant-ratio model and more parsimonious than elimination by aspects. To estimate this model in a spatial interaction context, a hierarchical regionalization based upon interareal flow data is first obtained. The lengths of the links in the resultant tree structure are reestimated on the basis of choice probability ratios.

A note on the use of aggregate data in individual choice models

1982 ◽  
Vol 18 (3) ◽  
pp. 313-335 ◽  
Author(s):  
Raymond S. Hartman
Keyword(s):  
Choice Models ◽  
Aggregate Data ◽  
Individual Choice

Choice Set Imputation in Atomistic Spatial Choice Models

2016 ◽  
Vol 2564 (1) ◽  
pp. 138-146 ◽  
Author(s):  
Alireza Zolfaghari ◽  
John Polak ◽  
Aruna Sivakumar
Keyword(s):  
Choice Models ◽  
Spatial Choice ◽  
Choice Set

scholarly journals Representing the Shape and Orientation of Destinations in Spatial Choice Models

2010 ◽  
Vol 30 (2) ◽  
pp. 119-137 ◽  
Author(s):  
Mark R. Ferguson ◽  
Pavlos S. Kanaroglou
Keyword(s):  
Choice Models ◽  
Spatial Choice

A Variety Seeking Model of Spatial Choice-Behaviour

1989 ◽  
Vol 21 (8) ◽  
pp. 1037-1048 ◽  
Author(s):  
A W J Borgers ◽  
R E C M van der Heijden ◽  
H J P Timmermans
Keyword(s):  
Utility Function ◽  
Choice Models ◽  
Choice Behaviour ◽  
Spatial Choice ◽  
Variety Seeking

Conventional choice-models are based on the assumption of a stable utility function. Previous studies have indicated that this assumption may be less valid for certain types of choice-behaviour. In this paper the idea of variety seeking is put forward as a possible explanation for varied choice-behaviour. A model is developed and tested in the context of recreational choice-behaviour.

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