The formulation of marketing strategy in urban public transport

This paper prescribes the parameters of marketing strategy formulation in the context of urban public transport and emphasises in particular the usefulness of the marketing mix and segmentation concepts. A marketing mix comprising the two primary dimensions of service attributes and promotion is advocated, the service attributes to include price, in-vehicle time, mesh density, frequency, reliability and comfort. Three primary trip purpose segments are identified viz. journey-to-work, shopping, and leisure/social trip segments, but these may be expanded into a twenty-four cell matrix once origin-destination and car access factors are included. The sensitivity of demand in these segments is examined mostly by reference to demonstration and experimental project data drawn from the United States and the United Kingdom. For the three primary trip purpose segments demand elasticity is shown to be greater for non-price than for price features; for both price and non-price service features elasticity is shown to be a function of journey purpose being least elastic for journey-to-work trips and most elastic for social/leisure trips. The role of promotion is examined and its importance to the successful marketing of public transport clearly demonstrated.This paper is a condensation of material appearing in The Management of Urban Public Transport: a marketing approach, by P. J. Hovell, W. H. Jones, and A. J. Moran, to be published by Saxon House and Lexington Books in 1975.     

The Contribution of Benefit-in-Kind Taxation Policy in Britain to the ‘Peak Car’ Phenomenon

Car use per person has historically grown year-on-year in Great Britain since the 1950s, with minor exceptions during fuel crises and times of economic recession. The ‘Peak Car’ hypothesis proposes that this historical trend no longer applies. The British National Travel Survey provides evidence of such an aggregate levelling off in car mileage per person since the mid-1990s, but further analysis shows that this is the result of counter trends netting out: in particular, a reduction in per capita male driving mileage being offset by a corresponding increase in female car driving mileage. A major contributory factor to the decline in male car use has been a sharp reduction in average company car mileage per person. This paper investigates this aspect in more detail. Use of company cars fell sharply in Britain from the 1990s up to the 2008 recession. Over the same period, taxation policy towards company cars became more onerous, with increasing levels of taxation on the benefit-in-kind value of the ownership of a company car and on the provision of free fuel for private use. The paper sets out the changes in taxation policy affecting company cars in the UK, and looks at the associated reductions in company car ownership (including free fuel) and patterns of use. It goes on to look in more detail at which groups of the population have kept company cars and in which parts of the country they have been most used, and how these patterns have changed over time. A preliminary investigation is also made of possible substitution effects between company car and personal car driving and between company car use and rail travel. Clearly, the role of the company car is only one of many factors that are contributing to aggregate changes in levels of car use in Great Britain, alongside demographic changes and a wide range of policy initiatives. But, company car use cannot fall below zero, so the effect of declining year-on-year company car mileage suppressing overall car traffic levels cannot continue indefinitely.     

Discerning the operational state of a vehicle’s distributed electronic systems from vehicle network traffic for use as a fault detection and diagnosis tool

This paper suggests a novel approach to finding faults in a vehicle’s electronic systems by monitoring the network traffic directly and generating statistical traits. The nature of the data in a CAN network is considered, and a case for the use of statistical analysis presented. Statistical traits extracted from the temporal behavior of network messages are investigated as a metric for fault detection. It is shown how this trait information can be extracted from network data, and how this information could be used for fault detection of an unknown fault on a CAN network. It is then demonstrated that combining multiple types of trait data can be used to correctly identify a fault once detected.