A robust approach for the infrastructural classification of railway stations in Tripura, India

Abstract

Infrastructural classification is a Decision-Making Unit (DMU) for the service providers to deliver better infrastructure. This paper intends to classify the infrastructural facilities of the railway stations offer to the passengers in Tripura through an alternative synthetic indicator. The study is based on both primary and secondary data. The existing synthetic indicator is also applied to it and generalisation of the indicator called generalised synthetic indicator is framed according to the nature of the observed data sets. The study reveals that stations are categorised into four different (very good, good, poor and very poor) infrastructural classifications due to frequency of passenger mobility, proximity of urban centers, location of industrial units, land use of hinterland and undulating topography of the site. The causal interference has been represented through geo-spatial technique. A policy recommendation is proposed to provide better railway infrastructure for the passengers.