scholarly journals Exploring the Factors That Impact on Transit Use through an Ordered Probit Model: The Case of Metro of Madrid

2016 ◽  
Vol 18 ◽  
pp. 35-43 ◽  
Author(s):  
Laura Eboli ◽  
Carmen Forciniti ◽  
Gabriella Mazzulla ◽  
Francisco Calvo
Author(s):  
Carmen Forciniti ◽  
Laura Eboli ◽  
Gabriella Mazzulla ◽  
Francisco Calvo

The configuration of urban areas is the result of a cyclic relationship between land use and transportation system: the changes in transportation system arrangements influence the localisation of residence and economic activities, as well as the changes in land use affect transportation system characteristics. In this context, by operating on land use, travel demand can be shift from the individual transportation modes to transit systems. In the literature, many conceptual models were proposed to describe the complex relationship between land use and travel behaviour. In addition to spatial variation, the study of travel demand shows the categorical variation of variables. This work aims to analyse the influence of the categorical variation of variables impacting on transit use. An ordered probit model is proposed for evaluating how transit use depends on variables related to socio-economic characteristics of population, territorial features, accessibility, and transportation system. The study case is Madrid metro network (Spain). The results show a strong influence of characteristics of population and land use variables on daily trips made using metro system and highlighted the aspects that mainly impact on the choice to travel by metro, providing useful suggestions for shifting people from individual transportation mode to transit systems.DOI: http://dx.doi.org/10.4995/CIT2016.2016.3205 


2018 ◽  
Vol 45 (8) ◽  
pp. 1142-1158 ◽  
Author(s):  
Tiken Das ◽  
Manesh Choubey

Purpose The purpose of this paper is to evaluate the non-monetary effect of credit access by providing an econometric framework which controls the problem of selection bias. Design/methodology/approach The study is conducted in Assam, India and uses a quasi-experiment design to gather primary data. The ordered probit model is used to evaluate the non-monetary impact of credit access. The paper uses a propensity score approach to check the robustness of the ordered probit model. Findings The study confirms the positive association of credit access to life satisfaction of borrowers. It is found that, in general, rural borrower’s life satisfaction is influenced by the ability and capacity to work, the value of physical assets of the borrowers as well as some other lenders’ and borrowers’ specific factors. But, the direction of causality of the factors influencing borrowers’ life satisfaction is remarkably different across credit sources. Research limitations/implications The study argues to provide productive investment opportunities to semiformal and informal borrowers while improving their life satisfaction score. Although the results are adjusted for selection and survivorship biases, it is impossible with the available data to assess which non-income factors explain the findings, and therefore this limitation is left to future research. Originality/value The study contributes to the literature of rural credit by assessing the probable differences among formal, semiformal and informal credit sources with respect to non-monetary impacts.


2012 ◽  
Vol 18 (3) ◽  
Author(s):  
Roos Haer

AbstractA range of theories have attempted to explain the variation in civilian abuse of warring parties. Most of these theories have been focused on the strategic environment in which these acts take place. Less attention is devoted to the perpetrators of these human right abuses themselves: the armed groups. This study tries to fill this niche by using the organizational process theory in which it is assumed that armed groups, like every organization, struggles for survival. The leader tries to ensure the maintenance of her armed group by increasing her control over her troops. The relationship between the level of control and the perpetrated civilian abuse is examined with a new dataset on the internal structure of more than 70 different armed groups around the world. With the help of a Bayesian Ordered Probit model, this new dataset on civilian abuse is analyzed. The results show that especially particular incentives play an important role.


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