Adapting Strategic Niche Management for evaluating radical transport policies--the case of the Durham Road Access Charging Scheme

Transport systems in the UK are facing severe problems of congestion, rising energy use and pollution. One response to this is the move from local authorities to gradually introduce Travel Demand Management (TDM)¹ strategies, but these measures involve a complicated set of institutions, processes, people and procedures.The old road-building transport policy regime involved a relatively simple system of actors and processes around which expertise, knowledge, and skills had built up over many decades. The result of this is particularly evident for more radical demand management measures (such as congestion charging, workplace parking fees and high occupancy vehicle lanes), which often get held up or discarded due to controversy, disagreements, unanticipated problems, and a whole host of delaying factors. If they ever get implemented, they tend to be watered-down and consequently less effective.One potential way to analyse these problems and identify possible solutions is the use of Strategic Niche Management (SNM). SNM is rooted in organisational innovation diffusion theory and provides a structure to evaluate and manage the introduction of new and innovative transport technologies. This paper introduces Strategic Niche Management and explores transferring this technique for evaluating TDM policy measures. The resulting technique is applied retrospectively to the case of the Durham Road Charging scheme, selected as an example for this paper.     

Congestion analysis of waterborne, containerized imports from Asia to the United States

A queuing model is introduced for estimating container flow times through port terminals as a function of infrastructure, staffing, and import volume. The model is statistically calibrated on industry data. Flow-time estimates of the model are aggregated with estimates from models previously developed for rail networks to develop estimates of the total container flow times from West Coast ports to inland distribution centers. Integrated with a supply-chain optimization model, the queuing formulas are used to predict import flows by port and landside channel in scenarios of total import growth, varying all-water rates, and a higher import share for nation-wide importers.     

Reprint of “Planning in feasible region by two-stage target-setting DEA methods: An application in green supply chain management of public transportation service providers”

To meet green supply chain management’s requirements of a company and its transportation service providers (TSPs), it is essential to set clear, achievable, and realistic targets. This paper proposes two data envelopment analysis (DEA) approaches to find targets for two-stage network structures. The objective of proposed approaches is to plan in feasible region. The feasible region specifies bounds to ensure targets are within current operational capacity of TSPs. Applying the approaches to set targets for 24 TSPs lead to different results. However, proposed models ensure that the TSPs would be efficient in their current capacity.