Formulation of revenue formula based on passenger demand pattern analysis

Abstract

In the past, Sri Lanka had a very systematic, developed and effective transport system compared to other Asian countries. The transportation modes like trains, buses, boats and tram cars provided a good interconnected transport system even in absence of sophisticated technology and information. Public transport is an essential service and is one of the most important components for well-being of growing and expanding areas. Public transport is a public service which is meant to provide service levels that comply with public demand. Since this is an industry, the sustainability purely depends on the organic cash generation of the business (internal flow). It is known and accepted that bus fares have to keep with rising prices ofinput to the bus industry and therefore fares have to be revised accordingly from time to time. The absence ofproper system to decide the rate ofthe fare revision, introduced a scientific way to decide the rate on the basis of operating cost through the bus fare policy in 2002. Currently the fare is decided on the basis of operating cost per km. The absence of a proper scientific revenue calculation creates an uncertainty about the fares based on costs. This study is an initial attempt to Formulation of Revenue Formula Based on Passenger Demand Pattern Analysis. Data for this study were gathered through past (historic) data extracted from ticket machines and way bills of Sri Lanka Transport Board and use of actual boarding alighting count data by conducting two onboard surveys. The first step is to analyze the current bus fares in different aspects such as historical view, current bus fares, section wise increments etc. Fares are the one and only contributor for revenue in bus industry. The identification of maximum load points carried out next. Main variables of Revenue Formula are number of passengers and coefficients. Coefficients mean the average incremental fare amounts applicable to each section additionally travelled by a passenger. The number of passengers was approximated using maximum load points and coefficients were calculated using probability matrices which show both the sections wise increments and passenger alighting patterns. On the basis of the results of this research, it can be concluded that the approximate revenue can be assessed based on passenger demand patterns.