The potential role of public–private partnerships in the upgrade of port infrastructure: normative and positive considerations

There is a broad consensus on the need for the major expansion of many ports. Traditionally, ports and related facilities have involved significant levels of direct or indirect government ownership or some degree of government financing. Most governments, however, are reluctant to either borrow money to fund the needed additional capital infrastructure or to fund it directly. Public–private partnerships (P3s) are thus an attractive potential option. But are they the answer? This article examines the normative rationales for P3s and presents a positive theory perspective that focuses on the conflicting goals of public and private partners. It argues that the major government impetus for P3s is likely to be for physical port infrastructure with moderate levels of market failure, such as small to medium sized ports, and not for intangible port activities. Furthermore, small to medium sized port P3s are likely to be successful in terms of having relatively low transaction costs and lower total social costs than alternative provision mechanisms. Nonetheless, even in this situation, the different goals of public and private partners may give rise to conflict. Drawing on the global empirical evidence on P3s, this article proposes some institutional design features that will help to ensure P3 success.     

Transport Network Design Problem under Uncertainty: A Review and New Developments

This paper aims to provide a state-of-the-art review of the transport network design problem (NDP) under uncertainty and to present some new developments on a bi-objective-reliable NDP (BORNDP) model that explicitly optimizes the capacity reliability and travel time reliability under demand uncertainty. Both are useful performance measures that can describe the supply-side reliability and demand-side reliability of a road network. A simulation-based multi-objective genetic algorithm solution procedure, which consists of a traffic assignment algorithm, a genetic algorithm, a Pareto filter, and a Monte-Carlo simulation, is developed to solve the proposed BORNDP model. A numerical example based on the capacity enhancement problem is presented to demonstrate the tradeoff between capacity reliability and travel time reliability in the NDP.     

Norm approximation method for handling traffic count inconsistencies in path flow estimator

Path flow estimator (PFE) is a one-stage network observer proposed to estimate path flows and hence origin–destination (O–D) flows from traffic counts in a transportation network. Although PFE does not require traffic counts to be collected on all network links when inferring unmeasured traffic conditions, it does require all available counts to be reasonably consistent. This requirement is difficult to fulfill in practice due to errors inherited in data collection and processing. The original PFE model handles this issue by relaxing the requirement of perfect replication of traffic counts through the specification of error bounds. This method enhances the flexibility of PFE by allowing the incorporation of local knowledge, regarding the traffic conditions and the nature of traffic data, into the estimation process. However, specifying appropriate error bounds for all observed links in real networks turns out to be a difficult and time-consuming task. In addition, improper specification of the error bounds could lead to a biased estimation of total travel demand in the network. This paper therefore proposes the norm approximation method capable of internally handling inconsistent traffic counts in PFE. Specifically, three norm approximation criteria are adopted to formulate three L_p-PFE models for estimating consistent path flows and O–D flows that simultaneously minimize the deviation between the estimated and observed link volumes. A partial linearization algorithm embedded with an iterative balancing scheme and a column generation procedure is developed to solve the three L_p-PFE models. In addition, the proposed L_p-PFE models are illustrated with numerical examples and the characteristics of solutions obtained by these models are discussed.     

Examining the scaling effect and overlapping problem in logit-based stochastic user equilibrium models

The purpose of this paper is to examine the scaling effect and overlapping problem in a route choice context using the logit-based stochastic user equilibrium (SUE) principle to explicitly account for the congestion effect. Numerical experiments are performed on nine models: the deterministic user equilibrium model, the multinomial logit SUE model with and without scaling, the C-logit SUE model with and without scaling, the path-size logit SUE model with and without scaling, and the paired combinatorial logit SUE model with and without scaling. Sensitivity analysis is conducted to examine the effects of route sets, congestion levels, dispersion intensities, and network asymmetries. A real transportation network in the City of Winnipeg, Canada is also used to compare the network equilibrium flow allocations of different SUE models. The results of the sensitivity analysis and the Winnipeg network reveal that both scaling effect and overlapping problem can have a significant impact on the network equilibrium flow allocations.     

Coastal management as a bargaining process

Abstract

Major challenges are ahead in managing the coastal zone of western Canada. Until now there has been no legislated focus through a coastal zone management act nor a policy for the management of coastal resources. Instead, policies and institutions have been evolving out of existing legislation responding to opportunities and needs as they have arisen. Management is predominantly a bargaining process the success of which depends on opportunities for informed participation by the affected interests. Considering the relatively small investments in management, bargaining appears to have worked rather well, but there are weaknesses. Fortunately, significant opportunities exist to improve performance at relatively low cost. In particular, there should be a shift from the past emphasis on inventorying, monitoring, and coordination, to the development of functional knowledge and sectoral planning that can be the basis for informed and representative bargaining.     

Impact of politics,economic events and port policies on the evolution of maritime traffic in Chinese ports

The Chinese government has been exploring various paths to find a direction that better suits China’s national conditions during the past 60 years. Meanwhile, a series of political and economic events and policy transformations have had different effects on the port industry. This article attempts to ascertain how these events and port policies have influenced Chinese port traffic through an empirical study on data covering 1952–2009. The findings suggest that foreign trade has been the prime driver of the throughput of Chinese ports. The increase in the ports’ throughput has enabled an increase in domestic demand and the urgent need for further port investment. Chinese port throughput has been subject to multiple shocks. The Great Leap Forward¹ is found to have had the largest, but only a short-term impact. China’s accession to the World Trade Organization, however, led to a longer and exclusive effect on ports, with little observed effect on the other variables. The reform of port governance is shown to have had a more lasting positive effect on port throughput than physical investment. However, these latter effects are minor, the economic and political factors remain the primary driving factors of port throughput.     

Estimating fuel consumption and emissions based on reconstructed vehicle trajectories

Microscopic emission models are widely used in emission estimation and environment evaluation. Traditionally, microscopic traffic simulation models and probe vehicles are two sources of inputs to a microscopic emission model. However, they are not effective in reflecting all vehicles' real‐world operating conditions. Using each vehicle's spot speed data recorded by detectors, this paper provides a new method to estimate all vehicles' real‐world activities data. These data can then be used as inputs to a microscopic emission model to estimate vehicle fuel consumption and emissions. The main task is to reconstruct trajectory of each vehicle and calculate second‐by‐second speed and acceleration from the activities data. The Next Generation Simulation dataset and the Comprehensive Modal Emissions Model are used in this study to calculate and analyze the emission results for both lane‐level and link‐level. The results showed that using the proposed method for estimating vehicle fuel consumption and emissions is promising. Copyright © 2012 John Wiley & Sons, Ltd.