Evaluating the impact of a newly added commuter rail system on bus ridership: a grouped ordered logit model approach

2019 ◽  
Vol 15 (2) ◽  
pp. 1081-1101 ◽  
Author(s):  
Moshiur Rahman ◽  
Shamsunnahar Yasmin ◽  
Naveen Eluru
Keyword(s):  
Logit Model ◽  
Ordered Logit ◽  
Ordered Logit Model ◽  
Commuter Rail ◽  
Rail System ◽  
The Impact ◽  
Model Approach

scholarly journals Analysis of Factors Influencing the Vehicle Damage Level in Fatal Truck-Related Accidents and Differences in Rural and Urban Areas

2016 ◽  
Vol 28 (4) ◽  
pp. 331-340 ◽  
Author(s):  
Li Linchao ◽  
Tomislav Fratrović
Keyword(s):  
Traffic Safety ◽  
Logit Model ◽  
Urban Areas ◽  
Information Criterion ◽  
Ordered Logit ◽  
Damage Level ◽  
Rural And Urban Areas ◽  
Ordered Logit Model ◽  
Rural And Urban ◽  
The Impact

Accidents involving large trucks very often end up with deadly consequences. Innocent people getting killed are acknowledged globally as one of the traffic safety greatest problems and challenges. While risk factors on truck-related accidents have been researched extensively, the impact on fatalities has received little or no attention, especially considering rural and urban areas, respectively. In this study, the generalized ordered logit model was used in Stata 11.0 to explore the complex mechanism of truck-related accidents in different areas. Data were obtained from The Trucks in Fatal Accidents database (TIFA). The Akaike Information Criterion (AIC) indicates that the model used in this paper is superior to traditional ordered logit model. The results showed that 9 variables affect the vehicle damage level in a fatal crash in both areas but with different directions. Furthermore, 23 indicators significantly affect the disabling damage in the same manner. Also, there are factors that are significant solely in one area and not in the other: 12 in rural and 2 in urban areas.

scholarly journals Air Transport Passengers’ Satisfaction: an Ordered Logit Model

2018 ◽  
Vol 33 ◽  
pp. 147-154 ◽  
Author(s):  
Maria Grazia Bellizzi ◽  
Laura Eboli ◽  
Carmen Forciniti ◽  
Gabriella Mazzulla
Keyword(s):  
Logit Model ◽  
Air Transport ◽  
Ordered Logit ◽  
Ordered Logit Model

scholarly journals Investigating the Impacts of Real-Time Weather Conditions on Freeway Crash Severity: A Bayesian Spatial Analysis

2020 ◽  
Vol 17 (8) ◽  
pp. 2768 ◽  
Author(s):  
Qiang Zeng ◽  
Wei Hao ◽  
Jaeyoung Lee ◽  
Feng Chen
Keyword(s):  
Real Time ◽  
Spatial Correlation ◽  
Logit Model ◽  
Weather Conditions ◽  
Crash Severity ◽  
Ordered Logit ◽  
Ordered Logit Model ◽  
Generalized Ordered Logit ◽  
Severity Levels ◽  
Generalized Ordered Logit Model

This study presents an empirical investigation of the impacts of real-time weather conditions on the freeway crash severity. A Bayesian spatial generalized ordered logit model was developed for modeling the crash severity using the hourly wind speed, air temperature, precipitation, visibility, and humidity, as well as other observed factors. A total of 1424 crash records from Kaiyang Freeway, China in 2014 and 2015 were collected for the investigation. The proposed model can simultaneously accommodate the ordered nature in severity levels and spatial correlation across adjacent crashes. Its strength is demonstrated by the existence of significant spatial correlation and its better model fit and more reasonable estimation results than the counterparts of a generalized ordered logit model. The estimation results show that an increase in the precipitation is associated with decreases in the probabilities of light and severe crashes, and an increase in the probability of medium crashes. Additionally, driver type, vehicle type, vehicle registered province, crash time, crash type, response time of emergency medical service, and horizontal curvature and vertical grade of the crash location, were also found to have significant effects on the crash severity. To alleviate the severity levels of crashes on rainy days, some engineering countermeasures are suggested, in addition to the implemented strategies.

scholarly journals A RANK-ORDERED LOGIT MODEL WITH UNOBSERVED HETEROGENEITY IN RANKING CAPABILITIES

2010 ◽  
Vol 27 (5) ◽  
pp. 831-846 ◽  
Author(s):  
Dennis Fok ◽  
Richard Paap ◽  
Bram Van Dijk
Keyword(s):  
Logit Model ◽  
Unobserved Heterogeneity ◽  
Ordered Logit ◽  
Ordered Logit Model

Use of ordered logit model with time series data for determining the factors affecting the milk yield of Holstein Friesians

2019 ◽  
Author(s):  
Özge Akkuş ◽  
Volkan Sevinç
Keyword(s):  
Time Series ◽  
Milk Yield ◽  
Logit Model ◽  
Time Series Data ◽  
Series Data ◽  
Ordered Logit ◽  
Factors Affecting ◽  
Ordered Logit Model ◽  
Lactation Length ◽  
Cattle Breeders

This article aims to introduce the use of ordered logit model with time series data in milk productivity studies and determine the important factor levels affecting the milk yield of Holstein Friesians. The data consists of 2002 records collected for the years 2009-2015 from the reports of the Cattle Breeders’ Association of Turkey (CBAT) in Muðla province in Turkey. The direct and marginal effects of the variables: parity, lactation length and year of calving on milk yield are investigated and the probabilities regarding the milk yield production for a given specific parity, lactation length and calving year are calculated. The results show that milk yield slightly increases on the 4th parity of cows. As far as the years concerned, although there had mostly been a steady amount of milk production between 2009 and 2015 years, there was a significant decrease in 2011 and increase in 2014.

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