What is behind fare evasion in urban bus systems? An econometric approach

Guarda, Pablo; Galilea, Patricia; Paget-Seekins, Laurel; Ortúzar, Juan de Dios

doi:10.1016/j.tra.2015.10.008

Cited by 30 publications

(26 citation statements)

References 13 publications

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“…Indeed, web-survey methods are powerful tools to gather data at low cost but the panel of the analysis could be biased as it is confined to passengers who have a web-connection. Besides, several passengers evade the fare as they do not have sufficient money to buy a ticket and/or a pass e.g., migrants, low-income people, as also shown in a recent analysis in Chile where the 42% rate of fare evasion is found in areas with the lowest socio-economic level [4]. Fourth, the on-board methodology has been preferred over mail and telephone owing to the higher response rates, the ability to collect data from those experiencing the service and so on [22].…”

Section: Research Context and Survey Methodsmentioning

confidence: 70%

“…On the one hand, to date, it is no surprise that a plethora of studies on fare evasion have focused attention on how to protect PTCs from monetary losses (Economic studies). This was achieved by evaluating changes to: ticketing systems infrastructure and management e.g., [4], [5]; policy and enforcement issues e.g., [6], [7], [8] and operational issues e.g., [9]. Besides, fare evasion can be associated with criminal behaviour of people.…”

Section: Introductionmentioning

confidence: 99%

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Segmenting Fare Evader Groups by Factor and Cluster Analysis

Salis¹,

Barabino²,

Useli³

2017

WIT Transactions on the Built Environment

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In proof-of-payment transit systems, fare evasion represents a crucial topic and undermines financial viability for public transport companies (PTCs). Two studies segmented all transit passengers by using qualitative research and explorative two-step cluster analysis as well as web-survey data. However, as far as the authors know, no study segmented exclusively the fare evader passengers, with the aim to know deeply characteristics of distinct groups, and to use data gathered from an intercept survey. Moreover, the combined use of a factorial and a cluster analysis was not adopted to solve this issue. By using 850 on-board personal interviews, gathered from an Italian PTC, a Multiple Correspondence Analysis and a Hierarchical Cluster Analysis have been performed to group the fare evader passengers. Three clusters of evaders' passengers are derived: 1) the chronic, 2) the calculated-risk and 3) the accidental fare evader. The chronic cluster includes passengers who always evade the fare, and represents a medium numerous groups of fare evaders. The calculated-risk cluster includes passengers who usually evade the fare and represents the most numerous group of evaders. The accidental cluster includes passengers who rarely evades the fare and represents the less numerous groups. These outcomes are very relevant and useful for both research and practice. Indeed, this paper contributes to the empirical understanding of the determinants of being a fare evader for a selected group. Moreover, it helps PTCs understand how evaders' groups differ each other, adopt suitable strategies for each group and evaluate their effects.

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Section: Research Context and Survey Methodsmentioning

confidence: 70%

Section: Introductionmentioning

confidence: 99%

Segmenting Fare Evader Groups by Factor and Cluster Analysis

Salis¹,

Barabino²,

Useli³

2017

WIT Transactions on the Built Environment

View full text Add to dashboard Cite

show abstract

“…Most published research has focused on explaining public transport fare evasion in terms of the existing infrastructure and other physical conditions (operating factors, vehicle characteristics, use of ticket barriers, etc.) and determining the best measures for reducing the evasion rate [3,7,[13][14][15][16][17][18][19].…”

Section: Literature Surveymentioning

confidence: 99%

“…Fare evasion on public transport systems is a worldwide problem, with multiple negative effects such as revenue losses, service quality reductions, and a deterioration in user perception of safety and security [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

“…Among the steps that have been taken is the creation of an anti-evasion unit, which developed an evasion reduction plan focused on such actions as more vigorous inspection and pursuit of evaders through bigger fines, increased ticket checks and the creation of an evader registry, as recommended by various authors [3,[6][7][8]. Unfortunately, none of these measures has had much success in mitigating the problem.…”

Section: Introductionmentioning

confidence: 99%

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Fare Evasion in Public Transport: Grouping Transantiago Users’ Behavior

2019

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A survey was conducted in July 2018 on the public bus system in Santiago, Chile, in which 457 users were asked to respond to a list of 42 statements expressing a range of attitudes on different aspects of the problem of fare evasion. The respondents were first categorized according to whether they had been observed paying or not paying the fare, and their responses were then subjected to separate cluster analyses that partitioned the respondents into groups according to their views on each survey statement. The analyses identified four distinguishable types or groups among those who did not pay the fare—radical, strategic, ambivalent, and accidental evaders—and three groups among those who did pay—proud, empathetic, and circumstantial evaders. The distinguishing factors motivating the decision to pay or not to pay the fare were found generally to reflect values and attitudes or ideologies but were also influenced by users’ perception of the social acceptability of evasion, the presence of anti-evasion measures, and how “organized” they were in taking care to have a farecard with them when planning to take a bus.

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Motive des Fahrens ohne (gültigen) Fahrschein

Schwerdtfeger¹

2019

Fahren Ohne (Gültigen) Fahrschein

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What is behind fare evasion in urban bus systems? An econometric approach

Cited by 30 publications

References 13 publications

Segmenting Fare Evader Groups by Factor and Cluster Analysis

Segmenting Fare Evader Groups by Factor and Cluster Analysis

Fare Evasion in Public Transport: Grouping Transantiago Users’ Behavior

Motive des Fahrens ohne (gültigen) Fahrschein

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