Nature of influence of out-of-vehicle time-related attributes on transit attractiveness: a random parameters logit model analysis

2014 ◽  
Vol 49 (5) ◽  
pp. 648-662 ◽  
Author(s):  
Mohammad Shafayat Hossain ◽  
John Douglas Hunt ◽  
S. C. Wirasinghe
Keyword(s):  
Logit Model ◽  
Model Analysis ◽  
Random Parameters ◽  
Random Parameters Logit

scholarly journals Heterogeneidad de preferencias y experimentos de elección: Aplicación de un logit con parámetros aleatorios a la demanda de nueces

2011 ◽  
Vol 4 (8) ◽  
pp. 105
Author(s):  
Dena M. Camarena ◽  
Ana I. Sanjuán
Keyword(s):  
Logit Model ◽  
Choice Experiment ◽  
Mixed Logit ◽  
Stated Preferences ◽  
Attribute Level ◽  
Random Parameters ◽  
Random Parameters Logit ◽  
Independence Of Irrelevant Alternatives

Consumers’ stated preferences towards walnuts are studied by means of a choice experiment, with a double objective: first, to identify the main attributes searched by consumer at purchase and second, to analyse the chances for the introduction into the Spanish market of the Pecan variety. From this study, commercial guidelines may be derived, that helps distribution and import companies to commercialise this nut. A mixed or random parameters logit is estimated which relaxes the IIA property (independence of irrelevant alternatives) present in the logit model with fixed parameters. In a mixed logit, coefficients of each attribute/level vary randomly across consumers, reflecting the heterogeneity of individuals’ preferences. This model also allows estimate efficiently the parameters when each individual chooses several times, as in the present study.

scholarly journals Investigating Rural Single-Vehicle Crash Severity by Vehicle Types Using Full Bayesian Spatial Random Parameters Logit Model

2021 ◽  
Vol 11 (17) ◽  
pp. 7819
Author(s):  
Fulu Wei ◽  
Zhenggan Cai ◽  
Zhenyu Wang ◽  
Yongqing Guo ◽  
Xin Li ◽  
...  
Keyword(s):  
Risk Factors ◽  
Spatial Correlation ◽  
Traffic Safety ◽  
Logit Model ◽  
Unobserved Heterogeneity ◽  
Crash Severity ◽  
Random Parameters ◽  
Crash Data ◽  
Random Parameters Logit ◽  
Single Vehicle

The effect of risk factors on crash severity varies across vehicle types. The objective of this study was to explore the risk factors associated with the severity of rural single-vehicle (SV) crashes. Four vehicle types including passenger car, motorcycle, pickup, and truck were considered. To synthetically accommodate unobserved heterogeneity and spatial correlation in crash data, a novel Bayesian spatial random parameters logit (SRP-logit) model is proposed. Rural SV crash data in Shandong Province were extracted to calibrate the model. Three traditional logit approaches—multinomial logit model, random parameter logit model, and random intercept logit model—were also established and compared with the proposed model. The results indicated that the SRP-logit model exhibits the best fit performance compared with other models, highlighting that simultaneously accommodating unobserved heterogeneity and spatial correlation is a promising modeling approach. Further, there is a significant positive correlation between weekend, dark (without street lighting) conditions, and collision with fixed object and severe crashes and a significant negative correlation between collision with pedestrians and severe crashes. The findings can provide valuable information for policy makers to improve traffic safety performance in rural areas.

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