State road transport undertakings in India: technical efficiency and its determinants
Purpose ‐ The purpose of this paper is not only to gauge the extent of technical efficiency in 31 state road transport undertakings (SRTUs) operating in India but also to explore the most influential factors explaining its variations across SRTUs. Design/methodology/approach ‐ Three popular data envelopment analysis (DEA) models, namely CCR, BCC and Andersen and Petersen's super-efficiency models, have been utilized to compute various efficiency scores for individual SRTUs. A censored Tobit analysis is conducted to see which factors significantly explain the inter-SRTU variations in efficiency. Findings ‐ The key findings of the DEA analysis are only five SRTUs define the efficient frontier, and the remaining 26 inefficient undertakings have a scope of inputs reduction, albeit by the different magnitude; the extent of average overall technical inefficiency (OTIE) in these SRTUs is to the tune of 22.8 percent, indicating that the sample SRTUs are wasting about one-fourth of their resources in the production operations; managerial inefficiency (as captured by the pure technical inefficiency) is a relatively more dominant source of OTIE; and operation in the zone of increasing returns-to-scale is a common feature for most of the undertakings. The multivariate regression analysis using Tobit analysis highlights that the occupancy ratio is the most significant determinant for all the efficiency measures, and bears a positive relationship with overall technical, pure technical and scale efficiencies. Further, scale efficiency is also impacted positively by the staff productivity. Practical implications ‐ The results of this paper can be applied from management's perspective. The managers can assess the relative efficiency of their SRTUs in the industry and take corrective measures to improve efficiency by altering input-output mix. Originality/value ‐ This paper provides more robust estimates of relative efficiency of the SRTUs and highlights the key determinants of overall technical efficiency.
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