Authors:
EKTA SINGH
DISHA MHATRE
SAKSHI LALWANI
Introduction:
Train delays represent a persistent challenge in rail travel, particularly in high-density networks like Indian Railways, where overcrowding, maintenance issues, and technical faults frequently disrupt passenger schedules. These delays not only heighten commuter stress but also lead to missed connections, economic losses, and reduced satisfaction with public transport. This problem underscores the need for better infrastructure and real-time communication to enhance reliability. Research into passenger perceptions via surveys can reveal key pain points and inform targeted improvements.
Objective:
To understand the perceptions of train delays.
Literature Review:
- Rezapour et al. (2021) examined the psychological effects of rail delays on passengers in Malaysia using surveys from 396 commuters, finding that delays trigger frustration, anger, and anxiety, which degrade perceived service quality, particularly when real-time information systems (PIS) provide inaccurate updates. The study highlights how uncertainty from delays amplifies negative emotions, emphasizing the need for reliable PIS to mitigate these impacts beyond mere time losses
- Preston et al. (2009) analysed delays in Great Britain’s rail network, distinguishing punctuality from cancellations, and noted a post-2000 deterioration followed by gradual recovery, with revealed preference data showing passengers’ relative insensitivity to delays in demand elasticities.
Data collection:
To understand the underlined phenomenon of the perceptions of train delays the following questions were framed with Likert scale:-
1. I feel significant stress when my train is delayed.
2. I find that real-time notifications effectively reduce my frustration.
3. I believe that poor maintenance causes more delays than weather conditions do.
4. I always plan extra buffer time in my schedule to account for potential delays.
5. I rely heavily on mobile apps to check for delay updates before reaching the station.
A google form was formed with the above questions on 5-point scale and responses were coded as 5-strongly agree,4-agree,3-nuetral,2-disagree,1-strongly disagree. Data was downloaded as an excel sheet and for every question’s mean, SD, Standard error and T-stat were calculated.
Data Analysis:
|
|
Q1 |
Q2 |
Q3 |
Q4 |
Q5 |
|
Mean |
3.61 |
3.84 |
3.79 |
3.43 |
3.68 |
|
SD |
0.69 |
0.62 |
0.68 |
0.751 |
0.73 |
|
SE |
0.06 |
0.06 |
0.07 |
0.074 |
0.07 |
|
T- Stat |
9.04 |
13.62 |
11.79 |
5.79 |
9.48 |
|
result |
Agree |
Agree |
Agree |
Agree |
Agree |
Conclusion:
1. People feel significant stress when the train is delayed(9.04).
2. People find that real-time notifications effectively reduce their frustration(13.62).
3. People believe that poor maintenance causes more delays than weather conditions do(11.79).
4. People always plan extra buffer time in their schedule to account for potential delays(5.79).
5. People rely heavily on mobile apps to check for delay updates before reaching the station(9.48).
References:
- Rezapour, M., et al. (2021). Rail Transport Delay and Its Effects on the Perceived Quality of Service. Transportation Research Record. PMCID: PMC8242956 PMID: 34220605
- Preston, J., et al. (2009). Impact of Delays on Passenger Train Services: Evidence from Great Britain. Transportation Research Record: Journal of the Transportation Research Board, 2117, 14-23.