Analysing the psychology behind fare evasion to overcome it
There are four types of fare dodgers depending on frequency, intentions, feelings and attitudes towards fare evasion

People in a subway
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Fare evasion -the act of traveling without a valid ticket- is a problem in many public transport systems around the world. It can reduce revenue in millions of dollars and undermine the financial viability of transit. However, there is little research to understand why people fare evade and, in turn, the best measures to adopt.

The Public Transport Research Group (PTRG) in Monash University (Melbourne, Australia)  filled in this gap and studied the reasons behind fare evasion. They first analysed the motivations to fare evade in Melbourne. Later, they expanded the scheme to other international cities such as London, New York and Toronto.

 

Types of fare dodgers

PTRG took into account frequency, intentions, feelings and attitudes towards fare evasion. Consequently they came across four types of fare dodgers: accidental evader, “it’s not my fault” evader, calculated risk-taker and career evaders. They all had similar rates and trends in the different international cities.

Graphic on the psychology behind fare evasion
Source: Delbosc A and Currie G (2016) ‘Four types of fare evasion: A qualitative study from Melbourne, Australia’ TRANSPORTATION RESEARCH PART F: TRAFFIC PSYCHOLOGY AND BEHAVIOUR Volume 43, November 2016, Pages 254–264

Conclusions were that “recidivists” –people who repeatedly intentionally fare evade– are a global problem. They represent a few portion of public transport frequent users. However, they account for most of fare loss.

 

Solutions to fare evasion

The study showed that the main motivation to fare evade is weak perceived control. Thus, it suggested increasing ticket inspections to tackle the issue. In fact, results showed that doubling control rates in Melbourne reduced fare evasion rate on tram by about 1/3 and allowed millions in additional revenue.

The report also pointed out emerging technologies. One of these mentions was for AWAAIT’s automatic real-time video analytics system DETECTOR. The tool, developed as part of TRAINSFARE project, uses Artificial Intelligence-Machine Learning algorithms to alert inspectors when it detects fare-dodging.

 

Deeper insight

For more information, you can take a look at Public Transport Research Group’s presentation “Revenue Protection – National and International Research Perspectives” here.