scholarly journals Weighted Variables Using Best-Worst Scaling in Ordered Logit Models for Public Transit Satisfaction

2020 ◽  
Vol 12 (13) ◽  
pp. 5318
Author(s):  
Iván Manuel Mendoza-Arango ◽  
Eneko Echaniz ◽  
Luigi dell’Olio ◽  
Eduardo Gutiérrez-González
Keyword(s):  
Logit Model ◽  
Multinomial Logit Model ◽  
Ordered Logit ◽  
Worst Case ◽  
Independent Variables ◽  
Public Transport System ◽  
Ordered Logit Model ◽  
Specific Attribute ◽  
Best Worst Scaling ◽  
Level Of Importance

Customer overall satisfaction regarding a public transport system is dependent on the satisfaction of the users with the attributes that make up the service, as well as the contribution that each of these attributes makes to explain the overall satisfaction. A common way of analysing the contribution of service attributes to explain overall satisfaction is through the use of ordered logit or probit models. This article presents an ordered logit model that considers the weighting of independent variables through the explicit importance calculated on the basis of a best-worst case 1 choice task. For the calculation of importance, a multinomial logit model has been estimated which considers the heterogeneity of the sample through systematic variations in user tastes. In this way, it is possible to establish a level of importance of each specific attribute for each type of user. The results show that the importance varies considerably depending on different socio-economic and mobility-base variables. On the other hand, the inclusion of the weighted variables in the ordered logit model improves its fit. Therefore, the results make possible to develop policies focused on improving satisfaction on specific user targets.

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.

Targeting Consumers for Exporting Rice to China by Ordered Logit Model Analysis

2017 ◽  
Vol 29 (4) ◽  
pp. 421-426
Author(s):  
Se-Hyuk Kim ◽  
◽  
Cheong-Ryong Lim ◽  
Hang-Ah Lee ◽  
Yun-Mi Oh ◽  
...  
Keyword(s):  
Logit Model ◽  
Model Analysis ◽  
Ordered Logit ◽  
Ordered Logit Model
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