In proof-of-payment transit systems, fare evasion has recently captured increasing attention because of the relevant implications it produces. Research has investigated how sociodemographic, travel behaviour, and situational determinants affect the intention to evade fares for segments of passengers clustered according to ‘Gender’ and ‘Age’. Conversely, no study has isolated these determinants in segments clustered according to ‘Employment’. This paper fills this gap by analyzing students, workers, and unemployed passengers. Key determinants are isolated by logistic regression models. The findings show that gender, age, and having been fined are the common determinants that make all these segments more likely to evade fares. In addition, some specific determinants are identified for each segment. Hence, the overall findings may support transit operators by anticipating preventive and corrective strategies tailored to specific segments, which can positively impact other segments.

Do students, workers, and unemployed passengers respond differently to the intention to evade fares? An empirical research

Barabino, Benedetto;
2020-01-01

Abstract

In proof-of-payment transit systems, fare evasion has recently captured increasing attention because of the relevant implications it produces. Research has investigated how sociodemographic, travel behaviour, and situational determinants affect the intention to evade fares for segments of passengers clustered according to ‘Gender’ and ‘Age’. Conversely, no study has isolated these determinants in segments clustered according to ‘Employment’. This paper fills this gap by analyzing students, workers, and unemployed passengers. Key determinants are isolated by logistic regression models. The findings show that gender, age, and having been fined are the common determinants that make all these segments more likely to evade fares. In addition, some specific determinants are identified for each segment. Hence, the overall findings may support transit operators by anticipating preventive and corrective strategies tailored to specific segments, which can positively impact other segments.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/533295
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