TY - JOUR
T1 - Policy-Driven Investigation of Sectoral Latent Information Regarding Global Road Fatalities
AU - Dimitriou, Loukas
AU - Nikolaou, Paraskevas
AU - Antoniou, Constantinos
N1 - Publisher Copyright:
© 2017 The Authors. Published by Elsevier B.V.
PY - 2017
Y1 - 2017
N2 - Road safety considerations correspond to an important element in the transport decision making and policy agenda, closely related to the increased valuation of human casualties in developed societies. Nevertheless, the expected raise of mobility, especially through private motorization, is putting a tough challenge on the decision/policy making that should be transferred from developed (in terms of road crash risk) and applied to developing (in the same terms) regions and countries. As reported in the relevant literature, the phenomenon of road traffic fatalities can be assigned to several factors that can be captured by several socio-economic factors. The current research aims on investigating the phenomenon of road traffic fatalities in a macro level and across the globe towards decision/policy making. For achieving this, a cardinal assumption investigated here relies on the fact that this complex phenomenon cannot be fully explained by a specific set of variables, giving raise to the assumption of unobserved, latent information. A solid methodological framework for incorporating observed and latent structures in a seamless manner, Structural Equation Modeling (SEM), is thus considered. As such, the objective of this study is to use an extensive database including socio-economic data (aiming on treating endogeneity), concerning 121 UN countries for the year 2013, within a SEM modeling framework.
AB - Road safety considerations correspond to an important element in the transport decision making and policy agenda, closely related to the increased valuation of human casualties in developed societies. Nevertheless, the expected raise of mobility, especially through private motorization, is putting a tough challenge on the decision/policy making that should be transferred from developed (in terms of road crash risk) and applied to developing (in the same terms) regions and countries. As reported in the relevant literature, the phenomenon of road traffic fatalities can be assigned to several factors that can be captured by several socio-economic factors. The current research aims on investigating the phenomenon of road traffic fatalities in a macro level and across the globe towards decision/policy making. For achieving this, a cardinal assumption investigated here relies on the fact that this complex phenomenon cannot be fully explained by a specific set of variables, giving raise to the assumption of unobserved, latent information. A solid methodological framework for incorporating observed and latent structures in a seamless manner, Structural Equation Modeling (SEM), is thus considered. As such, the objective of this study is to use an extensive database including socio-economic data (aiming on treating endogeneity), concerning 121 UN countries for the year 2013, within a SEM modeling framework.
KW - Global Road Fatalities
KW - Latent Data Structures
KW - Model Selection
KW - Structural Equation Modeling
UR - http://www.scopus.com/inward/record.url?scp=85019461538&partnerID=8YFLogxK
U2 - 10.1016/j.trpro.2017.03.067
DO - 10.1016/j.trpro.2017.03.067
M3 - Article
AN - SCOPUS:85019461538
SN - 2352-1457
VL - 22
SP - 685
EP - 694
JO - Transportation Research Procedia
JF - Transportation Research Procedia
ER -