Road transport safety is a major concern across Europe due to the human and socio-economic costs associated with work-related traffic accidents. Traditional approaches have adopted regulatory and technical measures to prevent road accidents leaving aside the organizational factors that might contribute to road transport safety. However, contemporary sociotechnical systems theory acknowledges the need to take into account organizational factors. This study adopts a sociotechnical approach and it examines the relationship between a number of organizational factors (organizational learning and training) and road traffic accidents in the organizations under study. Our sample was composed of 107 road transportation organizations from Spain. Binary logistic regression analyses were carried out to test our hypotheses. Organizational size and type of transport (goods or passengers) were included in the model as control variables. Results showed that in those organizations where organizational learning was supported, the occurrence of traffic accidents was less likely. Unexpectedly, the relationship between training and the occurrence of traffic accidents was not significant. Thus, findings partially supported the formulated hypothesis. Future research should shed light on the relationship between training and traffic accidents taking into account potential intervening variables.

The economics literature offers many examples of studies of the economic impact of transportation infrastructure such as highways, ports, and airports; however, little attention has been paid to other types of infrastructure such as logistics platforms. This article is a first assessment of the economic effects of the largest logistics platform in Europe – PLAZA, the Zaragoza Logistics Platform – located in Spain. More precisely, this paper analyzes the economic significance of PLAZA on the economy of the Aragon region where it is located. The methodology is based on the application of input–output analysis to the final demand of logistics platform-based companies in a manner that is similar to well-established studies of the economic impacts of tourism on tourist expenditure. This makes it possible to quantify the various levels of economic effects (direct, indirect, and induced) in terms of jobs, salaries, and wages, turnover, gross operating surplus (GOS), and gross value added (GVA). The conclusions reveal the economic importance PLAZA has for the regional economy of Aragon, representing just over 2% of total GVA and 3% of turnover.

In recent years, sustainable mobility policy analysis has used Hybrid Choice Models (HCM) by incorporating latent variables in the mode choice models. However, the impact on policy analysis outcomes has not yet been determined with certainty. This paper aims to measure the effect of HCM on sustainable mobility policy analysis compared to traditional models without latent variables. To this end, we performed mode choice research in the city of Santander, Spain. We identified two latent variables—Safety and Comfort—and incorporated them as explanatory variables in the HCM. Later, we conducted a sensitivity study for sustainable mobility policy analysis by simulating different policy scenarios. We found that the HCM amplified the impact of sustainable mobility policies on the modal shares, and provided an excessive reaction in the individuals’ travel behavior. Thus, the HCM overrated the impact of sustainable mobility policies on the modal switch. Likewise, for all of the mode choice models, policies that promoted public transportation were more effective in increasing bus modal shares than those that penalized private vehicles. In short, we concluded that sustainable mobility policy analysis should use HCM prudently, and should not set them as the best models beforehand.