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General Overview

EICS Framework

EMPOWERMENTELEVATIONFOUNDATION

Region of Reference

  • AfricaAfrica
  • AsiaAsia
  • AustraliaAustralia
  • EuropeEurope
  • North-AmericaNorth-America
  • South-AmericaSouth-America
  • WorldWorld

Description

This type of intervention entails communicating when a service is delayed, as a result of the disruption. Disruptions in public transport are typically caused by technical component failures or insufficient resource allocation, which can be caused by planned maintenance actions, disruptions to infrastructure and disruptions to the transport system's operation, or some unexpected events, such as track failures, rolling stock failures, staff, and power supply failures, and weather [3]. Disruptions can have a substantial impact on passengers' travel and also force travellers to make vital decisions, such as rescheduling or even cancelling the trip [4].

With the introduction of GPS, smartphones, and digital social networking, the nature and method of contact between public transportation service providers and their consumers have shifted dramatically [5]. Social media has been found to have distinct advantages over traditional information systems when it comes to communication during times of uncertainty [5,6]. According to an assessment of passenger experiences with unanticipated service disruptions in the United Kingdom (UK), the most critical information needs of consumers during unforeseen service interruptions were the duration and cause of delays, as well as alternative modes of transport. A lack of communication during uncertain times may lead to criminals, including perpetrators of sexual harassment acts becoming more active.

Types of Impact

Area Impacted

  • To/from the stop/station/rank
  • Waiting for train/bus/paratransit
  • In the vehicle
  • At interchanges
This intervention would impact areas where formal infrastructure is present and would also impact areas on the way to the stop/station, on the vehicle and at interchanges.

Time of Day of Impact

  • Day-time travel
  • Night-time travel
  • Peak-time travel
  • Off peak-time travel
All travel time categories could be positively impacted by this intervention, depending on the scale of implementation. This is especially true for peak-hour travel, as this intervention has the potential to cut waiting and travel times when passengers are informed of interruptions, i.e., when consumers avoid unnecessary journeys to public transportation systems that are experiencing disruptions.

Mode Impacted

  • Bus
  • Train
  • Rideshare
  • 4 wheelers informal
  • 3 wheelers informal
  • 2 wheelers informal
  • Cycling
  • Walking
This intervention could impact all formal transport systems, except for individual non-motorised transport, as they have the capabilities and potentially the infrastructure to implement communication structures to inform users of disruptions.

Demographic impacted

  • Girls
  • Boys
  • Adult Women
  • Men
  • Elderly Women
  • LGBTQI+
All public transport users could be positively impacted by this intervention, if information is made available in a timely manner, this could result in reduced travel time for all affected passengers, regardless of their demographic.

SWOT Analysis

  • Improvement in user experience, information makes it possible to find alternative transport mode or avoid travel

  • Convenient and fast to use

  • Reduction in delays caused by disrupted system

  • As soon as implementation stops, the benefits stop

  • Budget restrictions may limit expenditure

  • Integration of ticketing systems to ensure seamless transfer to alternative mode during disruption

  • Technology is constantly evolving

  • Potential need to transfer when using alternative service, adding an interchange and new scope for offences to occur

  • Misinformation, even distributed by criminals

  • Long delays may embolden perpetrators who now feel they have time to commit their offences

Effectiveness

During disruptions the risk of sexual harassment increases, as well as the anxiety regarding potential sexual harassment or other security threats. Being able to make informed decisions empowers women to mitigate the increased (perceived) risk.

  • Perception by (female) passengers
  • Perception by governing bodies
  • Level of confidence in these ratings

Implementation

Implementing this intervention does not take time as the communication can be integrated into the already established communication means. Developing new communication platforms can be a once-off time consuming activity. Dissemination of information should, however, be instant once the systems are in place. Benefits arise while the intervention is carried out and continue to accumulate as passengers are exposed to it.

Implementation timeframe

  • 0-1 year
  • 1-3 years
  • >3 years

Timeframe to realise benefits

  • 0-1 year
  • 1-3 years
  • >3 years

Scale of Implementation

This intervention can be implemented at a station/suburb or city level.

National
Regional
City
Station or
Suburb

Ease of Implementation

This intervention is moderately easy to implement if the technology to support it is in place. Developing those support systems first can make it more difficult to implement.

List of References

Africa

Africa

1. Pender B, Currie G, Delbosc A, Shiwakoti N. Social media utilisation during unplanned passenger rail disruption - What’s not to “Like”? Australas Transp Res Forum, ATRF 2013 - Proc. 2013;(October):1-14.

World

World

3. Leng N, Corman F. The role of information availability to passengers in public transport disruptions: An agent-based simulation approach. Transp Res Part A Policy Pract. 2020;133(December 2019):214-236. doi:10.1016/j.tra.2020.01.007

4. Adelé, S., Tréfond-Alexandre, S., Dionisio, C., Hoyau PA. Exploring the behavior of suburban train users in the event of disruptions. Transp Res Part F Traffic Psycholology Behav. 2019;65:344-365.

5. Cottrill C, Gault P, Yeboah G, Nelson JD, Anable J, Budd T. Tweeting Transit: An examination of social media strategies for transport information management during a large event. Transp Res Part C Emerg Technol. 2017;77:421-432. doi:10.1016/j.trc.2017.02.008

6. Pender B, Currie G, Delbosc A, Shiwakoti N. Social Media Use during Unplanned Transit Network Disruptions: A Review of Literature. Transp Rev. 2014;34(4):501-521. doi:10.1080/01441647.2014.915442