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As the land transport task, especially road is expected to increase significantly, by 2015, it would hardly be surprising that many policy makers will look to some form of urban transport environmental control long before this date. One method is via the introduction of a set of operational environmental hurdles. This is not a new concept. However, this paper proposes a new environmental initiative for urban transport operations. The scheme which is simple for both operators and regulators proposes an effective and meaningful operational rating system which reflects the efforts an operator may go to in their internal fleet environmental policies in purchasing equipment, daily workload planning, waste disposals policies etc.

The three tiered environmental operator performance rating scheme, the E-plus scheme has three levels of operator segmentation. A good basic auditable level of environmental compliance, an E rating, an excellent rating E plus, and an exceptional rating would be an E double plus. Probably no fleets currently in Australia would earn a double plus rating at this time.

Why should there be a road transport operator environmental rating scheme? Firstly as a measurable benchmark for the community and the fleet operators themselves. Secondly and a factor of growing importance is for the customers who are the buyers of freight services. Already customers are specifying in their tender requirements that transport operator environmental competencies and capabilities be listed. This may aid the selection of an operator for a specific task. For example; food sensitive freight handling may require specific food certification scheme adoption such as the HACCP classification system. Similarly an urban courier contract may specify, environmental credentials which sit under an ISO 14000 framework. However, what more specific operator differentiation criteria can be requested by the customer? The E plus system is being designed for this very purpose. In Australia some regulators and teaching centres have begun to take an interest in this transport operator framework.

More than ever before, public transit must compete in the transport market. This competition is, on the one hand, against steadily increasing car traffic; and on the other hand, between public transit operators. This, in turn, leads to new demands regarding the type, content and quality of data needed for planning and management. Frequently, traditional travel behaviour surveys do not provide sufficiently accurate and detailed information about public transit demand. To plan public transit, frequently a precise description of all trip stages, including the first and the last mile, is necessary. To achieve this, an adaptation of the traditional survey methods is necessary. In many countries, public transit associations have been established to integrate services offered by individual public transit operators with the help of through-ticketing and a coordination of lines and timetables into what looks, to the user, like a single system. To distribute revenue among the operators involved, detailed surveys of passengers are needed. Measuring the quality of public transit service and surveying customer satisfaction are new tasks. Such data are the basis for quality assurance and are essential for gaining and keeping customers of the public transit system. New technologies such as the Global Positioning System, automated passenger counts and Smart Card Payment Systems offer new possibilities to collect data more efficiently and cost-effectively. This article covers essential aspects of surveys and the collection of data that are crucial for the planning and management of public transit; it points to state-of-the-art methods and offers potential solutions.

The purpose of this paper is to investigate contracts of the intermodal transport market and the incentives they create for a modal shift and thus the financial and environmental efficiency of freight transport.

The research used a mixed-methods approach where qualitative case interviews and quantitative modeling was combined. Two cases of contractual relationships between a service provider and its intermodal train operator on a specific lane were investigated. The case findings were then consolidated and used as input for a model of the contractual relation. Findings were sought through an extensive numerical study.

The cases reported that intermodal rail operators had a strong production focus, transferring the capacity risk (i.e. the risk of unused capacity) to the service provider, which the service providers argued limited the shift from truck to intermodal transportation. The paper shows that, due to the market structure, it is rational for the operator to transfer the capacity risk but not the profit. Consequently, a modal shift is only likely to occur when there is strong shipper pressure or low capacity risk. We present a risk-sharing contract that could release this dead lock.

The conclusions are modeling outcomes subject to assumptions based on the cases. For further validation, large-scale quantitative studies are necessary.

The paper shows that a three-part tariff in which the capacity risk is shared may lead to increased modal shift and hence assumed improved environmental performance.

Instead of arguing for operators to be more customer-focussed, policy makers and other stakeholders may have more to gain by having both actors being more cooperation focussed.

The paper is the first attempt to quantify how the contractual relations on the freight transport market affect the modal mix and thus the financial and environmental efficiency of freight transport.

This chapter demonstrates how the ‘golden rule’ can be applied by operators of flexible transport services to improve investment and pricing decisions.

The chapter explains why an appropriate decision making framework is particularly important for operators of flexible transport services and compares the traditional economic framework of fixed versus variable costs to the decision-oriented approach that analyses the activities of a firm in terms of costs that are avoidable (i.e. specific to a particular activity) and costs that are shared amongst a number of activities. The chapter introduces the ‘golden rule’ of decision making and discusses issues in implementing the rule.

An economic framework for decision making is particularly important for smaller scale transport operations (such as flexible transport services) because ‘lumpy’ investment costs are more significant than for larger operators. The traditional economic approach divides costs into fixed costs and those which vary by patronage. A better framework for decision making divides costs into those which are specific to a particular activity and, therefore, avoidable if that activity ceases, and those costs which are common to more than one activity.

Using this framework allows operators to apply the ‘golden rule’ in pricing their services so that the avoidable costs of each activity are recovered and the enterprise covers its shared costs overall.

This chapter will be useful to operators of flexible transport services who are new to the industry or are reacting to changes in the funding environment.

This chapter presents a novel visualisation tool, known as Flexible Integrated Transport Services (FITS) that transport commissioners, providers and administrators could employ to specify and edit the operating constraints as they redesign transport services.

The context of rural transport planning is discussed noting that where resources are fewer, effective co-ordination is required to provide passengers with efficient transport services. An overview of the FITS visualisation tool and its different sub-systems (e.g. general information regarding services, operating area, passenger eligibility, fare structure and surcharge structure) is given. Additionally, some key computational details of the system are discussed. Preliminary results of a sample case study that trialled the FITS tool in a specific test run, using simulated transport to health data in the Morayshire and North-West Aberdeenshire area of Scotland are presented. The concluding discussion considers the potential impact of employing tools like FITS in planning transport services in rural and low-demand settings.

Results from the case study show how these effects could be quantified in terms of changes in costs incurred by transport providers, the level of potential demand that could be covered and the associated revenues (fares and subsidies) which could be generated by providers.

The FITS visualisation tool has the potential to act as a planning tool to help transport commissioners, providers and administrators visualise the effects of shifting operating boundaries of flexible transport services.

This chapter presents a review of community transport in Australia with the aim of providing material for comparative research in flexible transport.

Research on Australian community transport has been brought together to present an analysis of the key features of the industry: history; geography; funding; regulation and the use of volunteers.

Each key feature has led to the current strong state/territory basis for service organisation and delivery, despite the federal responsibility for supplying most of the funding and ensuring equity and standards. Varying approaches to regulation and supply have also been driven by remoteness and the prevalence of large pockets of entrenched social disadvantage in some regions.

The chapter summarises research findings including hitherto unpublished research on an application of flexible transport services outside mainstream public transport operations in Australia.