Susana Freiria

This article discusses public transport fare evasion from the point of view of the relations between inspection actions and detected evasion, with the aim of improving the efficacy of the former. By applying spatial statistics methods to a large dataset from Lisbon, Portugal, namely, entropy-based local bivariate relationships (LBR) and geographically weighted regression (GWR), it is shown that the two variables are associated in a widespread manner throughout the city, mostly in a linear way. Mapping out marginal gains from inspection actions then shows where they detect the most evaders, allowing transport companies to relocate their inspector teams in a more effective manner. Results for Lisbon show that gains in effectiveness of circa 50% can be obtained, mostly by moving some inspector teams from the centre of the city to the periphery during daytime. The methodology requires only inspection/detection databases, which transport companies usually have, making it a valuable, practical tool to combat fare evasion.

This article presents a large case study of fare evasion on bus lines in the city of Lisbon, Portugal, a common problem in dense urban areas. Focus is put on geographic factors, and an analysis is carried out using a generalized spatial two-step least-squares regression (GS2SLS). The large database, spanning one year of fare evasion reports, made it possible to segregate the analysis according to type of day (workday or weekend) and time period (rush hours, nighttime, etc.). Results show that indeed the type of day and time period lead to considerable differences between the seven models analyzed. It was found that the number of inspection actions is the strongest predictor of evasion, with geographic factors also playing a role in predicting fare evasion. Consideration of this spatial component made it possible to find moderate evidence for dissuasive effects of inspection actions in some models and of pockets of evasive tendencies in other models, which appear in the statistical error term. Interestingly, and contrary to other studies, age was found to have almost no influence on the propensity to evade fares. From a managerial point of view, this study highlights the importance of running inspection actions systematically and closely monitoring their outcomes. From a more theoretical standpoint, it suggests further research on geographic factors is needed to fully understand spatial patterns of evasion.

The decision of TAP was rightly seen as a downgrade of Oporto Airport's position in TAP's network, motivating harsh public reaction from several businessmen and politicians, including the mayors of Oporto and of several municipalities of the Norte Region. Besides the Norte Region, it encompasses large parts of the Centro Region and of Galicia. Summing up, the results of our study indicate that Oporto Airport activity has influenced in a significant way the economic performance of the three areas of the Norte Region. The chapter analyses the impact of Oporto Airport on the economy of the Norte Region between 2000 and 2016, considering different sectors and how this impact was felt in three different areas of the region at different distances from the airport. It provides the evidence that Oporto Airport activity had a significant impact on the economic performance of the Norte Region in the period under analysis.

This article addresses the problem of the multiscale importance of road networks, with the aim of helping to establish a more resilient network in the event of a road disruption scenario. A new model for identifying the most important roads is described and applied on a local and regional scale. The work presented here represents a step forward, since it focuses on the interaction between identifying the most important roads in a network that connect people and health services, the specificity of the natural hazards that threaten the normal functioning of the network, and an assessment of the consequences of three real-world interruptions from a multiscale perspective. The case studies concern three different past events: road interruptions due to a flood, a forest fire, and a mass movement. On the basis of the results obtained, it is possible to establish the roads for which risk management should be a priority. The multiscale perspective shows that in a road interruption the regional system may have the capacity to reorganize itself, although the interruption may have consequences for local dynamics. Coordination between local and regional scales is therefore important. The model proposed here allows for the scaling of emergency response facilities and human and physical resources. It represents an innovative approach to defining priorities, not only in the prevention phase but also in terms of the response to natural disasters, such as awareness of the consequences of road disruption for the rescue services sent out to local communities.