Incorporating Latent Variables into Discrete Choice Models — A Simultaneous Estimation Approach Using SEM Software

Temme, Paulssen, Dannewald, 2008, in Business Research

doi:10.1007/BF03343535
Location Germany
Population General
Sample size 519
Factor analysis type confirmatory factor analysis, none rotation
Stepwise regression no
Removal of insignificant variables no
Reviewed by LCM

Abstract

Integrated choice and latent variable (ICLV) models represent a promising new class of models which merge classic choice models with the structural equation approach (SEM) for latent variables. Despite their conceptual appeal, applications of ICLV models in marketing remain rare. We extend previous ICLV applications by first estimating a multinomial choice model and, second, by estimating hierarchical relations between latent variables. An empirical study on travel mode choice clearly demonstrates the value of ICLV models to enhance the understanding of choice processes. In addition to the usually studied directly observable variables such as travel time, we show how abstract motivations such as power and hedonism as well as attitudes such as a desire for flexibility impact on travel mode choice. Furthermore, we show that it is possible to estimate such a complex ICLV model with the widely available structural equation modeling package Mplus. This finding is likely to encourage more widespread application of this appealing model class in the marketing field. © 2008, The Author(s).

Factors

Models

Dependent variable Mode choice
Model type MNL
Sample size 519.0
R2 nan
Adjusted R2
Pseudo R2 (McFadden) 0.07
AIC 23741.0
BIC 23853.0
Log-likelihood at zero nan
Log-likelihood at constants nan
Log-likelihood at convergence -11766.0
Car and PT
Variable Coefficient p-value
Distance bus -0.03 0.478
Distance other PT -0.13 0.034
Age 0.0 0.952
Gender -0.41 0.178
Income -0.08 0.127
Mode constant -0.62 0.318
Car and PT, car only
Variable Coefficient p-value
Travel time car -1.62 0.009
PT only
Variable Coefficient p-value
Distance bus -0.09 0.472
Distance other PT -0.12 0.014
Age 0.0 0.897
Gender 0.06 0.849
Income -0.11 0.047
Mode constant -0.72 0.318
PT only, car and PT
Variable Coefficient p-value
Travel time PT -1.16 0.009
Dependent variable Mode choice
Model type ICLV
Sample size 519.0
R2 nan
Adjusted R2
Pseudo R2 (McFadden) 0.115
AIC 23724.0
BIC 23843.0
Log-likelihood at zero nan
Log-likelihood at constants nan
Log-likelihood at convergence -11752.0
Car and PT
Variable Coefficient p-value
Flexibility -0.39 0.037
Convenience/comfort 0.54 0.065
Safety -0.19 0.308
Distance bus -0.03 0.562
Distance other PT -0.13 0.035
Age 0.0 0.734
Gender -0.4 0.208
Income -0.02 0.742
Mode constant -0.64 0.338
Car and PT, car only
Variable Coefficient p-value
Travel time car -1.51 0.021
Convenience/comfort
Variable Coefficient p-value
Power 0.21 0.036
Hedonism 0.28 0.014
Security 0.62 0.0
Age -0.08 0.413
Gender 0.04 0.522
Income 0.01 0.873
Flexibility
Variable Coefficient p-value
Power 0.25 0.005
Hedonism 0.15 0.049
Security 0.36 0.004
Age -0.16 0.076
Gender 0.05 0.413
Income 0.23 0.0
Hedonism
Variable Coefficient p-value
Age -0.25 0.0
Gender -0.09 0.086
Income -0.14 0.004
PT only
Variable Coefficient p-value
Flexibility -0.44 0.005
Convenience/comfort 0.61 0.04
Safety -0.57 0.003
Distance bus -0.1 0.46
Distance other PT -0.11 0.02
Age 0.0 0.81
Gender 0.12 0.719
Income -0.03 0.66
Mode constant -0.89 0.272
PT only, car and PT
Variable Coefficient p-value
Travel time PT -1.24 0.009
Power
Variable Coefficient p-value
Age 0.08 0.151
Gender -0.15 0.003
Income 0.06 0.304
Safety
Variable Coefficient p-value
Power 0.1 0.106
Hedonism 0.16 0.019
Security 0.25 0.004
Age 0.1 0.156
Gender 0.1 0.064
Income 0.05 0.304
Security
Variable Coefficient p-value
Age 0.47 0.0
Gender 0.04 0.51
Income -0.05 0.358

The Attitudes and Travel Database is produced with support from the Center for Teaching Old Models New Tricks at Arizona State University, a University Transportation Center sponsored by the US Department of Transportation through Grant No. 69A3551747116.

sha256:a08d9e369743bf7e6d1c40d27347318209b40a7fb1543813fdcf31b898918815