1,721,222 research outputs found
Mobility Management at manager and employer level through a web-based system and its application
No full textA modified model to curb fare evasion and enforce compliance: empirical evidence and implications
No full textFare evasion is a major problem for transit companies due to lost fare revenues and damage to their corporate images. Therefore, the establishment and proper management of ticket inspection teams deployed to tackle fare dodgers is highly important and represents a severe challenge. In this paper, an existent profit maximization model for estimating the optimum level of inspection has been extended, calibrated, and tested in a real case, using data available from an Italian transit operator, resulting from 98 days of checks and 3659 completed on-board interviews. Given the current network-wide inspection level per single verifier, and considering the level of fines currently applied, the optimal value of the total inspection rate is found to amount to 4.5%. The model provides empirical evidence towards understanding the fare evasion problem, besides highlighting the need for collaboration with the managers of the transit company. An overview of the manipulation of some control variables related to risk perception and the main implications of the findings are presented to transport companies using “honour” ticketing systems
Application of Mobility Management: a Web structure for the optimisation of the mobility of working staff of big companies
No full textThis study deals with the application of a Web structure available to both Mobility Managers and employees. Its main functionalities enable the Mobility Manager to collect mobility data that can be used to design some optimal home-to-work mobility strategies and the employees to access a car pooling service. The realisation of this Web structure has been made possible by using, as support tools, Intelligent Transportation System Technologies such as Geographic Information System and Web services beside a communication network. The realisation of the application has been preceded by a pilot survey carried out within an industrial area in South Sardinia. The survey results have highlighted the need for an organised management of the home-to-work mobility, as well as the sample’s willingness to use viable alternatives to private car use. In
this article, the modules related to the on line questionnaires and the car pooling service are investigated. With reference to the car pooling service, the functioning of the matching algorithm has been tested by using the pilot survey results and is
described in the appendix. The testing results show that the response times for the algorithm are acceptable for home-to-work trips, within the territorial context investigated in this research
Assessing the Intention to Evade Fares for Demographic Segments of Passengers: Empirical Research in Italy for Building Smart(er) Cities
No full textA strong interest in fare evasion is currently emerging in all proof-of-payment transit systems owing to its severe implications. Recent research has investigated from the passenger perspective how sociodemographic variables, travel behavior, and situational factors affect the intention to evade fares for students, workers, and unemployed passengers. Conversely, testing the demographic segmentation of passengers clustered according to gender and age variables and isolating the key factors related to the intention to evade fares have not yet been addressed. Besides the context of the smart cities' paradigm, the fight against fare evasion has been little dealt with, also owing to the difficulty in being able to frame such an issue within the classic pillars of smartness. This study covers these gaps using a two-step approach. First, gender and age variables are used to define five demographic segments: male, female, young, middle-aged, and older passengers. Next, crucial determinants are detected for each segment using statistical models. The analysis revealed that the intention to evade fares increases for males who travel a lot during the day and for females who are dissatisfied with the service and know the fine amount. Moreover, it increases for young, middle-aged, and older passengers that make short trips, often travel, and use various transit systems, respectively. Finally, the intention to evade fares increases for each segment when passengers have a history of fare evasion. The overall findings may help bus operators plan tailored countermeasures against specific segments
Evasione tariffaria nel trasporto pubblico locale: livello ottimo di ispezione ed implicazioni. Un contributo empirico
No full textUn confronto in termini economici dei “Metodi di priorità” per il trasporto collettivo urbano
No full textSegmenting fare-evaders by tandem clustering and logistic regression models
No full textIn this study, a tandem clustering is applied on data collected by an Italian public transport company. Three clusters of evader passengers are discovered. Next, for each cluster, the influence of significant determinants in evaluating the chance of being a frequent fare evader is shown by logistic regression models. Members of Cluster 1 are a small segment of choice-workers, who seldom evade fares significantly. Members of Cluster 2 represent a big segment of captive students, who often evade the fare. Members of Cluster 3 are a medium segment of captive unemployed, who always evade the fare. The logistic regression models show that attributes related to the situational factors are significant, and honesty is the common variable that significantly affects the chance of being a frequent fare evader among segments. These outcomes are relevant and useful for both research and practice. Indeed, this paper contributes to the empirical understanding of the determinants of being a frequent fare evader for segments a posteriori selected. Moreover, it helps PTCs to better understand how some segments differ from each other
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