Evaluating Public Transport Efficiency: A Cross-Regional SFA Approach

Bus-based public transport systems are considered to provide affordable means of transport to trip-makers in urban and rural areas. Consequently, public transport organizations are prone to losses since these agencies focus on providing mobility to people on commercially viable routes while providing accessibility and mobility to underdeveloped remote regions. The primary objective of this study was to effectively use a parametric approach, such as Stochastic Frontier Analysis (SFA), in the evaluation of the performance of public transport organizations operating in India. The present study employed nine key performance indicators (KPIs) to evaluate 31 State Road Transport Undertakings (SRTUs) in India over a period of seven years (2010-2017). The nine KPIs, such as total cost, staff, fleet, fuel, capacity-km, effective-km, passenger-km, revenue, and passengers carried, were used to develop three performance measurement categories: cost efficiency, cost-effectiveness, and service effectiveness. After developing 29 initial models, the best ones were selected based on Akaike's Information Criterion (AIC) and Bayesian Information Criteria (BIC), and performance evaluation of SRTUs was carried out with the SFA approach using the Cobb-Douglas production function. The study revealed that the top 25 percentile of best-performing SRTUs in terms of cost-efficiency were those serving rural areas with average efficiency scores higher than 0.7668. Similarly, in terms of cost-effectiveness, it was observed that the best-performing SRTUs comprised a mix of both rural and urban SRTUs with average efficiency scores higher than 0.9156. Also, in terms of service-effectiveness, the best-performing SRTUs included buses operated mainly in urban areas in addition to a few serving hilly and rural areas with average efficiency scores higher than 0.6509. The findings of this study provide insights into the performance of SRTUs in India and highlight the importance of using KPIs to evaluate and improve their performance. This study also demonstrates the effectiveness of using the SFA in the performance evaluation of public transport organizations, especially when the data related to the KPIs are partially inconsistent. This is due to the facility that permits the formulation of a production function that assists in identifying random errors, allowing the replacement of erroneous data.