scholarly journals Using a General Ordered Logit Model to Explain the Influence of Hotel Facilities, General and Sustainability-Related, on Customer Ratings

2020 ◽  
Vol 12 (21) ◽  
pp. 9302 ◽  
Author(s):  
Ioana-Nicoleta Abrudan ◽  
Ciprian-Marcel Pop ◽  
Paul-Sorin Lazăr
Keyword(s):  
Logit Model ◽  
Negative Influence ◽  
Ordered Logit ◽  
Rating Systems ◽  
Explanatory Variables ◽  
Ordered Logit Model ◽  
Electric Vehicle Charging ◽  
Proportional Odds Assumption ◽  
Charging Stations ◽  
Generalized Ordered Logit Model

The hotel market has become extremely competitive over the past years. Hotels try to differentiate themselves through their services and facilities. To make the best choice when searching for accommodation, guests increasingly use rating systems of booking sites. Using an ordered logit model (OLM), we identify, in our study, a sample that comprises of 635 hotels from Romania. These are the hotel facilities that significantly influence customer review scores (as an expression of customer satisfaction) on booking.com, the most widespread rating system. We also identify whether their impact on intervals of satisfaction levels vary. Some explanatory variables invalidate the Brant test for proportional odds assumption. Thus, for the final estimates, we use a generalized ordered logit model (GOLOGIT). The results show that food-related facilities, restaurants, and complimentary breakfasts, are very significant for customer ratings. Relevant hotel common facilities are the pool and parking spaces, while for the room—the flat-screen TV. It is interesting to note the negative influence of pets, which seem to disturb other tourists. In the sustainability category, only facilities for disabled people and electric vehicle charging stations are relevant.

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 Understand e-bicyclist safety in China: Crash severity modeling using a generalized ordered logit model

2018 ◽  
Vol 10 (6) ◽  
pp. 168781401878162 ◽  
Author(s):  
Tao Wang ◽  
Jun Chen ◽  
Chen Wang ◽  
Xiaofei Ye
Keyword(s):  
Traffic Control ◽  
Logit Model ◽  
Injury Severity ◽  
Age Groups ◽  
Industrial Area ◽  
Ordered Logit ◽  
The Road ◽  
Ordered Logit Model ◽  
Generalized Ordered Logit ◽  
Generalized Ordered Logit Model

A thorough crash modeling effort was made to examine e-bicyclists’ injury severity, using a generalized ordered logit model, which can capture the ordinal nature of injury severity and allow for heterogeneity across observations. A number of factors associated with injury severity of e-bicyclists are identified, including older e-bicyclists, heavy truck involved, e-bicyclist at fault, e-bicyclist turn left, e-bicyclist cross the road, driver turn right, industrial area, weekday, and tree separation. Safety countermeasures and interventions are thus proposed based on the modeling results, including developing educational programs for specific age groups (e.g. older e-bicyclists, female e-bicyclists, and inexperienced drivers), launching safety campaigns, improving geometric design and traffic control in low-developed area, curve roads, and signalized intersections. Moreover, some interesting research topics are also suggested, such as examining head-on e-bike crash mechanism, crash mechanism between e-bicyclists and heavy trucks and motorcycles, and safety effects of different separation treatments on e-bicyclists’ injury severity from kinetic and kinematic perspectives.

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