The application of regression analysis on users’ tolerance to prolonged waiting times: the case of KTM Komuter Services of Malaysia

Bachok, S.; Osman, M. M.; Khalid, U. A.; Zainaldin, M. F. · 2012 · OpenAlex-citations

DOI: 10.2495/cr120251

archive: archived pipeline: cataloged verified

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Summary

This study investigates passenger tolerance to prolonged waiting times and service inconsistencies within the KTM Komuter rail system in Kuala Lumpur, Malaysia. Motivated by widespread issues such as traffic congestion, poor punctuality, and inadequate service quality that hinder the shift from private vehicles to public transport, the research aims to quantify how users perceive and tolerate delays. The authors seek to identify factors influencing this tolerance to assist operators and regulators in planning system improvements. The methodology involved primary data collection through semi-structured questionnaires distributed to 1,000 KTM Komuter users between November 2011 and February 2012. The survey captured socio-demographic data, trip characteristics, and perceptions of service quality. Statistical analysis was conducted using SPSS, employing exploratory data analysis, multivariate correlations, and regression analysis. Specifically, a bivariate regression model was developed with waiting time as the dependent variable and years of experience using the service as the independent variable. Cross-tabulation analyses were also performed to assess relationships between waiting time and variables such as frequency of use, travel duration, and travel purpose. The findings reveal a high level of tolerance among commuters, particularly captive riders during peak hours. Descriptive analysis showed that respondents experienced maximum waiting times of up to 150 minutes, with half unable to board the first train during peak periods. The regression model indicated a weak but statistically significant relationship between years of experience and waiting time ($R^2 = 0.013$). Cross-tabulation results demonstrated moderate to high associations between waiting time and factors such as the number of trains waited for, total travel time, and travel purpose; notably, users traveling for shopping or sightseeing exhibited higher tolerance than those traveling for work or education. The study also highlighted that ticketing inefficiencies added up to 25% to total journey time, and overcrowding was a persistent issue due to low frequency (15–30 minutes) and inadequate coach capacity. The significance of this research lies in its provision of empirical models that quantify user tolerance, offering actionable insights for service providers. The authors conclude that addressing inefficiencies such as delays, poor punctuality, and ticketing bottlenecks is critical to preventing a decline in ridership. Recommendations include increasing train frequency, adding coaches to reduce overcrowding, improving maintenance to minimize breakdowns, and enhancing ticketing systems. These measures are deemed essential for improving service reliability and encouraging mode switching from private cars to public transport, thereby alleviating urban traffic congestion.

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