scholarly journals A Freight Mode Choice Analysis Using a Binary Logit Model and GIS: The Case of Cereal Grains Transportation in the United States

2012 ◽  
Vol 02 (02) ◽  
pp. 175-188 ◽  
Author(s):  
Guoqiang Shen ◽  
Jiahui Wang
Author(s):  
Aleida Cobas-Valdés ◽  
Ana Fernández-Sainz

ABSTRACTThe aim of this paper is to study the educational self-selection problem of Cuban migrants to the United States. For the analysis, we specify and estimate a binary logit model to analyze the observable covariates that explain migration probability. The data used in the study came from the United States Census of Population and Housing of 2010, and from the Cuba Census of Population and Housing of 2002. The results indicate that education, age and occupational covariates explain migration probability. Moreover, there is a positive educational self-selection problem, that is, migrate those people with more educational level. The principal contribution of this paper is demonstrate that a high level educational increases the probability to emigrate.RESUMENEn este artículo se analiza el problema de la autoselección educativa de los emigrantes cubanos a Estados Unidos. Para el análisis hemos especificado y estimado un modelo logit binario a fin de identificar las variables obser-vables que influyen en la probabilidad de emigrar. Los datos utilizados provienen del Censo de Población y Vivienda de Estados Unidos del año 2010 y del Censo de Población y Vivienda de Cuba del año 2002. Los resultados indican que las variables educación, edad y categoría ocupacional explican la probabilidad de emigrar. Además, se produce una autose-lección positiva en cuanto al nivel educativo de los individuos, es decir, emigran los que más años de educación poseen. La principal aportación de este artículo consiste en demostrar que un alto nivel de educación incrementa la probabilidad de emigrar de los cubanos.


2020 ◽  
Vol 12 (22) ◽  
pp. 9522
Author(s):  
Phattarasuda Witchayaphong ◽  
Surachet Pravinvongvuth ◽  
Kunnawee Kanitpong ◽  
Kazushi Sano ◽  
Suksun Horpibulsuk

Increasing use of single or fewer occupant vehicles has increased traffic congestion and transport-related emissions. Public transport as mass transit options are increasingly being encouraged amongst travelers to use, as this is an influential strategy to improve the transport network performance. This paper presents a study based on a revealed preference survey conducted on a random sample of 4467 respondents to understand the influential factors affecting the users’ choice of mass transit in Bangkok, Thailand. This study identified an inversely proportional relationship of socio-economic and spatial attributes on public transport mode choice. The binary logit model was employed to compare the utility of private vehicles and mass transit modes. The results showed that gender, age, average income, auto ownership, total travel cost in private transport, total travel time in public transport and distance range from home to mass transit station were the factors that influenced travelers’ mode choice behavior. Moreover, to ascertain the effects of explanatory variables which influence the likelihood of Thai travelers, another binary logit model analysis was utilized by the four distance ranges condition. The studied results showed that there were few significant differences in the propensity to use mass transit. Due to the longer distance of the station, total travel time in public transport was not affected by the Thai travelers mode choice. This research will aid transport authorities and planners to gain knowledge on the impact of socio-economic and spatial behavior of public transport users on their mode choice, resulting in the development in sustainable transport in Bangkok, Thailand.


2019 ◽  
Vol 270 ◽  
pp. 03013 ◽  
Author(s):  
Anggit Cahyo ◽  
Nahry ◽  
Helen Burhan

Beside the ridesoucing service, ridesplitting service is also offered by Transport Network Companies (TNC). The ridesplitting service have more benefit than ridesourcing because it is using the concept of carsharing. The current condition for ridesplitting service is not popular and only have small demand than ridesourcing service. This study aims to establish a mode choice model between ridesourcing and ridesplitting service in DKI Jakarta and to estimate the potential of demand shifting from ridesourcing to ridesplitting service in DKI Jakarta. The mode choice model is developed from binary logit model with stated preference survey using fare saving, additional time travel and security presented by gender parameter of ridesplitting service. the sensitivity of logit model show that highest sensitivity rate to increase mode switching to ridesplitting service is in 20% to 50% fare saving level. The probability of current condition to switch to ridesplitting service is 20%.


Author(s):  
O. C. Puan ◽  
Y. A. H. Hassan ◽  
N. Mashros ◽  
M. K. Idham ◽  
N. A. Hassan ◽  
...  

2019 ◽  
Vol 11 (10) ◽  
pp. 39
Author(s):  
Jean D. Gumirakiza ◽  
Mara E. Schroering

Online shopping is changing ways in which offline markets operate. As the online shopping for fresh produce takes off, it is important to investigate its effects on existing physical market outlets. The main objective for this study is to explain how often online shoppers attend farmers’ markets. The study uses data that was collected in 2016 from a sample of 1,205 consumers residing in the south region of the United States who made at least two online purchases within six months prior to participating in this study. This study employed a multinomial Logit model and Stata was used to run the regression. Results show that the majority of these online shoppers never attended a farmers’ market. The relative probabilities for the online shoppers to “never” attend farmers’ markets, attend “occasionally”, and “frequently” are 0.54, 0.28, and 0.18 respectively. We found that the lack of awareness, inconvenient place and/or time, and low interests are major reasons for nonattendance. This study suggests that farmers’ markets could greatly benefit by developing marketing strategies targeting online shoppers.


Author(s):  
Babak Mirbaha

Pedestrian safety has become a serious problem with the rapid growth of motorised vehicle in transportation system in developing counties. Pedestrians often respond differently to changes in surrounding and traffic conditions. A study was undertaken to investigate pedestrians’ gap acceptance and the parameters affecting their risk-taking behaviours based on time-to-collision and post-encroachment-time indexes. Three signalised intersections and two midblock crossings were selected in Qazvin, Iran. A total of 752 pedestrians were examined by video recording and field observation, and pedestrians’ gap acceptance behaviour was estimated by using binary logit model. Results showed that the average time to collision and post-encroachment time were 4.27 s and 1.44 s, respectively. In addition, the presence of children alongside the older pedestrians led to a less risk-taking crossing. Additionally, pedestrian risk-taking was reduced by increasing both time indexes. Rainy weather also reduced pedestrians’ risk-taking behaviour. Elasticity analysis indicated that parameters such as pedestrians’ conflict with vehicles at the first or second half of the crossings, walking with a child, speed of the approaching vehicle, the crossing type and running while crossing were the most important factors in pedestrian risk-taking.


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