Cost escalations in the front-end of projects – empirical evidence from Norwegian road projects

This paper investigates an issue largely ignored in the transport literature on cost overruns, namely, cost increases in the early project phase, long before the decision to build is made. This is the phase of project planning that is referred to as the front-end phase in the literature. The rationale of the study is that unless cost estimates during the front-end phase are relatively accurate, the wrong projects may be selected for further development. We first argue for why it is important to address cost escalation during the front-end phase of project planning. We then use Norwegian data to demonstrate the magnitude of cost escalations during the front-end phase of projects and in comparison to the implementation phase. We find that even in a sample of projects with relatively small cost overruns as in the case of Norway, there are substantial cost increases before the formal decision to build was made. This raises the issue of whether decisions and priorities taken at the early stages of project development are based on false information and whether this may lead to the wrong project concepts being selected.     

学术语篇中情态模糊限制语及其评价意义研究

学术语篇常被认为以客观方式传递信息和表达观点．但其撰写者若要达到这种目标,并使语篇中的信息和观点能充分地被读者所认可或接受,需借用一定的语言表达手段．情态模糊限制语便是其中的表达手段之一．基于此,试从系统功能语言学中的评价理论出发,对学术语篇中情态模糊限制语及其评价意义进行研究．     

Air transportation in a carbon constrained world: Long-term dynamics of policies and strategies for mitigating the carbon footprint of commercial aviation

With increasing demand for air transportation worldwide and decreasing marginal fuel efficiency improvements, the contribution of aviation to climate change relative to other sectors is projected to increase in the future. As a result, growing public and political pressures are likely to further target air transportation to reduce its greenhouse gas emissions. The key challenges faced by policy makers and air transportation industry stakeholders is to reduce aviation greenhouse gas emissions while sustaining mobility for passengers and time-sensitive cargo as well as meeting future demand for air transportation in developing and emerging countries. This paper examines five generic policies for reducing the emissions of commercial aviation; (1) technological efficiency improvements, (2) operational efficiency improvements, (3) use of alternative fuels, (4) demand shift and (5) carbon pricing (i.e. market-based incentives). In order to evaluate the impacts of these policies on total emissions, air transport mobility, airfares and airline profitability, a system dynamics modeling approach was used. The Global Aviation Industry Dynamics (GAID) model captures the systemic interactions and the delayed feedbacks in the air transportation system and allows scenarios testing through simulations. For this analysis, a set of 34 scenarios with various levels of aggressiveness along the five generic policies were simulated and tested. It was found that no single policy can maintain emissions levels steady while increasing projected demand for air transportation. Simulation results suggest that a combination of the proposed policies does produce results that are close to a “weak” sustainability definition of increasing supply to meet new demand needs while maintaining constant or increasing slightly emissions levels. A combination of policies that includes aggressive levels of technological and operations efficiency improvements, use of biofuels along with moderate levels of carbon pricing and short-haul demand shifts efforts achieves a 140% increase in capacity in 2024 over 2004 while only increasing emissions by 20% over 2004. In addition, airline profitability is moderately impacted (10% reduction) compared to other scenarios where profitability is reduced by over 50% which pose a threat to necessary investments and the implementation of mitigating measures to reduce CO2 emissions. This study has shown that an approach based on a portfolio of mitigating measures and policies spanning across technology and operational improvements, use of biofuels, demand shift and carbon pricing is required to transition the air transportation industry close to an operating point of environmental and mobility sustainability.     

Assessment of large transport infrastructure projects: The CBA-DK model

This paper presents a newly developed decision support model to assess transport infrastructure projects: CBA-DK. The model combines use of conventional cost–benefit analysis to produce aggregated single point estimates, with quantitative risk analysis using Monte Carlo simulation to produce interval results. The embedded uncertainties within traditional CBA such as ex-ante based investment costs and travel time savings are of particular concern. The paper investigates these two impacts in terms of the Optimism Bias principle which is used to take account of the underestimation of construction costs and the overestimation of travel time savings. The CBA-DK methodological approach has been used to apply suitable probability distribution functions on the uncertain parameters, thus resulting in feasibility risk assessment moving from point to interval results. The proposed assessment model makes use of both deterministic and stochastic based information. Decision support as illustrated in this paper aims to provide assistance in the development and ultimately the choice of action, while accounting for the uncertainties surrounding transport appraisal schemes. The modelling framework is illustrated by the use of a case study appraising airport and runway alternatives in the capital of Greenland – Nuuk. The case study has been conducted in cooperation with the Home Rule Authorities of Greenland.     

A spatial Difference-in-Differences estimator to evaluate the effect of change in public mass transit systems on house prices

Evaluating the impact of public mass transit systems on real-estate values is an important application of the hedonic price model (HPM). Recently, a mathematical transformation of this approach has been proposed to account for the potential omission of latent spatial variables that may overestimate the impact of accessibility to mass transit systems on values. The development of a Difference-in-Differences (DID) estimator, based on the repeat-sales approach, is a move in the right direction. However, such an estimator neglects the possibility that specification of the price equation may follow a spatial autoregressive process with respect to the dependent variable. The objective of this paper is to propose a spatial Difference-in-Differences (SDID) estimator accounting for possible spatial spillover effects. Particular emphasis is placed on the development of a suitable weights matrix accounting for spatial links between observations. Finally, an empirical application of the SDID estimator based on the development of a new commuter rail transit system for the suburban agglomeration of Montréal (Canada) is presented and compared to the usual DID estimator.     

Multi-criteria impacts assessment for ranking highway projects in Northwest Spain

This paper presents a multi-criteria model to rank highway projects by predicting their combined potential impact on regional population, economy, environment, territory and mobility. A detailed study of initial conditions enable the selection of functional units of study and the identification of homogenous units within the region, playing a relevant role into the process. Ranking is based on the achievement of both efficiency and cohesion objectives at a regional level. The model is tested by analyzing the Spanish Transport Infrastructure Master Plan (PEIT) for the non-central area of Northwest Spain. Application of impact assessment shows that the construction of infrastructures has selective effects in the area according to the homogenous groups. Potential development was boosted in one of the zone groups, whereas in others, at best, there was a reduction in their regressive tendency. Finally, the model is a dynamic support tool that could be adapted to several planning policies only when the ranking criterion is well-justified.     

Agent-based modelling for assessing hybrid and electric cars deployment policies in Luxembourg and Lorraine

Electric mobility is often presented as a way to tackle the environmental issues associated with individual mobility, provided that electric vehicles are adopted by drivers on a mass scale. In this paper, we propose an agent-based model (ABM) aiming at modelling the deployment of these vehicles. ABM is particularly indicated when modelling complex systems whose final results are the combination of the interactions between individuals and their environment and when the agents have partial information to take their decisions. We selected Luxembourg and its French neighbouring region, Lorraine, as the case study for our model, to test Luxembourg’s ambitious objective of deploying 40,000 electric vehicles by the year 2020. Model results show that the number of battery powered electric vehicles in Luxembourg (including vehicles from Lorraine’s commuters crossing the border every day) could be between 2000 and 21,000. A high number of commercial vehicles in Luxembourg, as well as an unlikely deployment in the neighbouring Belgium and Germany would therefore be required to meet the deployment objective. However, the deployment of plug-in hybrid vehicles could reach 60,000 cars by the end of 2020. To achieve this number, the deployment of charging points seems to be the more effective policy, along with actions aiming at increasing public awareness and acceptance of electric vehicles. The interest in using the ABM also lies in the identification of the main individuals’ characteristics affecting the deployment of electric vehicles (household size, commuting distances, etc.), which further support the setting of public policies.     

Methodologies to monetize the variations in load factor and GHG emissions per passenger-mile of airlines

Global GHG emissions from air travel are currently at 3% and it could increase to 15% of the total GHG emissions by 2050. To curb the growth of GHG emissions from air travel, the U.S. Federal Aviation Administration (FAA) has created a policy to achieve carbon neutral growth by 2020 relative to the 2005 baseline. If the airline industry is to both grow and meet the objectives set by this policy, new and innovative aircraft designs, operational efficiencies, and widespread use of alternate fuels are required. To accomplish this would require large research and development investment. The federal government and state governments have passed legislations that provide tax breaks and other incentives to encourage investments in new technologies. One such tax policies is cap and trade system. This had partial success in reducing GHG emissions in certain industries but was not successful in the airline industry. This paper presents alternate methods to raise capital to invest in GHG emissions reduction projects in the airline sector. The four methodologies presented here monetizes the GHG emissions resulting from differences in load factor (ratio of number of passengers to number of seats) and GHG emissions per passenger-mile among different airlines, among different flight sectors, etc. to raise the capital. Based on 2012 air travel data, these methodologies could raise more than $300 million dollars annually to invest in GHG emissions reduction projects.     

AN APPROACH TO THE ECONOMIC APPRAISAL OF AVCS MAGLEV

The purpose of an economic appraisal of a transportation project is to help select an efficient transportation investment plan. Here, efficiency means achieving the best transportation service from a given investment and the generation of net benefits at least as great as the costs of the investment. In this article, three future transportation investment alternatives in the USA are compared using the benefit-cost ratio method to illustrate the economic desirability of the AVCS Maglev alternative – an advanced vehicle control system based on magnetic levitation and propulsion. For the completeness of the economic appraisal and the provision of a guide to performing non-user benefit analysis for this promising ITS technology, the socioeconomic effects of implementing AVCS Maglev in the USA are evaluated based on the US National Development Model (NDM).     

A Stated preference freight mode choice model

Transport policy aims to assist the transport system to work more efficiently and effectively. An understanding of the reasons why people choose to move freight in a certain manner is critical to the development of appropriate policies. This article outlines a data collection approach and the development of a disaggregate mode choice model applicable to the analysis of freight shipper decision making. It focuses on the choice between rail and road in Java, Indonesia. The model indicates that safety, reliability and responsiveness are major attributes influencing rail/road freight mode choice. Transport policies aimed at improving these dimensions should increase the attractiveness of rail transport.