The assessment of market efficiency in the shipping sector: a new approach

The aim of this paper is to use an alternative measure of the efficiency of the different shipping industries, i.e. VLCC/ULCC (250000dwt), Suezmax (140000dwt), Aframax (80000dwt), which are the main carriers of crude oil, and Handymax (40000dwt), which carries the vast majority of clean (oil) products. The results of the theoretical analysis confirm that, under pure expectations theory, the larger vessels demonstrate higher volatility, as measured by the standard deviation, than the smaller vessels, thereby supporting the proposition that period freight rates do indeed appear to be perfect foresights of the future spot rates.     

Investor herding behaviour in globally listed shipping stocks

ABSTRACT

This study undertakes one of the first empirical attempts to investigate and contribute a set of innovative findings to investor herding behavior and herding spillover effects in globally listed shipping company stock returns. Distinguishing between OECD and Non-OECD markets, herding behavior is tested on a diversified set of shipping companies traded in international equity markets, over different business cycle phases, financial crises, and external shocks. A set of dynamic models, well established in the relevant behavioral finance literature, is implemented. Empirical evidence indicates investor herding behavior in shipping stock returns and herding spillover effects between different shipping sectors, albeit not robust in all cases. These challenging findings can have a material impact on efficient investment and financing decisions of shipping market players.     

Marina inventory and berthing supply projections: Mississippi's Gulf Coast

Abstract

The location as well as pace of marina development is a major issue in current coastal zone management. The supply and demand for marinas providing certain services in specific locations are growing and must be met. At the same time the environmental integrity of the coastal zone must be maintained against the many possible impacts of marina development. Compounding these problems from the view of both the developer and coastal zone manager is the absence of necessary data and accepted methodologies for estimating future supply needs for marine berthing. This paper describes a multi‐focii approach to the establishment of an information base and marina supply projections for the Mississippi Gulf Coast. Data on existing marina types, services, and facilities are obtained via fieldwork; future marina slip supply needs are estimated using a combination of several techniques and data sources. The study serves two purposes. First, it initiates the basis for improved management of marina development on Mississippi's Gulf Coast. Second, on a more theoretical level, it stimulates research toward developing and validating supply and demand projection techniques for marinas.     

Mobile phone use by young drivers: effects on traffic speed and headways

Abstract

This paper investigates the effects of mobile phone use while driving on traffic speed and headways, with particular focus on young drivers. For this purpose, a field survey was carried out in real road traffic conditions, in which drivers' speeds and headways were measured while using or not using a mobile phone. The survey took place within a University Campus area, allowing to distinguish between settings approximating to either free flow or interrupted flow conditions. Linear and loglinear regression methods were used to investigate the effects of mobile phone use and several other young driver characteristics, such as gender, driving experience and annual distance travelled, on vehicle speeds and headways. Separate models were developed for average free flow, interrupted flow, as well as for total average speed. Results show that mobile phone use leads to a statistically significant reduction in traffic speeds of young drivers in all types of traffic conditions. Furthermore, male and female drivers reduce their speed similarly when using a mobile phone while driving. However, male drivers using their mobile phone drive at lower speeds than female drivers not using their mobile phones. Sensitivity analysis revealed that, among all explanatory variables, the effect of mobile phone use on speed was most important. Accordingly, vehicle headways appear to increase for drivers using their mobile phone. However, this effect could not be statistically validated, due to the strong correlation between speed and headway.     

Investigating the predictive performance of computational process activity-based transportation models

The aim of this paper is to achieve a better understanding of computational process activity-based models, by identifying factors that influence the predictive performance of A Learning-based Transportation Oriented Simulation System model. Therefore, the work activity process model, which includes six decision steps, is investigated. The manner of execution in the process model contains two features, activation dependency and attribute interdependence. Activation dependency branches the execution of the simulation while attribute interdependence involves the inclusion of the decision outcome of a decision step as an attribute to subsequent decision steps. The model is experimented with by running the simulation in four settings. The performance of the models is assessed at three validation levels: the classifier or decision step level, the activity pattern sequence level and the origin–destination matrix level. The results of the validation analysis reveal more understanding of the model. Benchmarks and factors affecting the predictive performance of computational activity-based models are identified.     

Citizen Participation and Collaborative Environmental Management in the Marine Oil Trade of Coastal Alaska

This study compares the contributions to policy change made by two Regional Citizens’ Advisory Councils that participate in the environmental management of the marine oil trade in coastal regions of Alaska. Both councils are remarkably well-funded and long-enduring examples of citizen participation in environmental policy. This study finds that both councils have applied their substantial funding resources to make significant contributions to policy change (policy contributions) in the marine oil trade of coastal Alaska. This study also finds that both councils have greatly magnified their policy contributions through collaborative efforts with many other organizations active in the marine oil trade of Alaska. Therefore, the overall policy contributions of the councils result from the joint application of council resources and collaborative efforts.     

Assessing appropriate stiffness levels for spudcan foundations on dense sand

Before a jack-up can operate at a given location, a site-specific assessment of its ability to withstand a design storm during operation must be performed. During this assessment, the complex state of stress and strain under a spudcan is usually simplified to a value of foundation stiffness that is integrated as a boundary condition into the structural analysis. Soil stiffness is a critical parameter affecting the foundation and structural load distribution and displacements, and the jack-up natural period and dynamic response. The level of spudcan stiffness is an area of intense interest and debate. This paper assesses appropriate stiffness levels for numerical simulation. Utilising results from a detailed “pushover” experiment of a three-legged model jack-up on dense sand, the paper compares the experimental pushover loads and displacements on the hull and spudcans to numerical simulations using different assumptions of spudcan stiffness. These include pinned and encastré footings, linear springs and a force-resultant model based on displacement-hardening plasticity theory. Constant stiffness levels are shown to be inadequate in simulating the experimental pushover test. The non-linear degradation of stiffness associated with the latter force-resultant model is critical.     

Bayesian calibration of mechanistic aquatic biogeochemical models and benefits for environmental management

Aquatic biogeochemical models have been an indispensable tool for addressing pressing environmental issues, e.g., understanding oceanic response to climate change, elucidation of the interplay between plankton dynamics and atmospheric CO₂ levels, and examination of alternative management schemes for eutrophication control. Their ability to form the scientific basis for environmental management decisions can be undermined by the underlying structural and parametric uncertainty. In this study, we outline how we can attain realistic predictive links between management actions and ecosystem response through a probabilistic framework that accommodates rigorous uncertainty analysis of a variety of error sources, i.e., measurement error, parameter uncertainty, discrepancy between model and natural system. Because model uncertainty analysis essentially aims to quantify the joint probability distribution of model parameters and to make inference about this distribution, we believe that the iterative nature of Bayes' Theorem is a logical means to incorporate existing knowledge and update the joint distribution as new information becomes available. The statistical methodology begins with the characterization of parameter uncertainty in the form of probability distributions, then water quality data are used to update the distributions, and yield posterior parameter estimates along with predictive uncertainty bounds. Our illustration is based on a six state variable (nitrate, ammonium, dissolved organic nitrogen, phytoplankton, zooplankton, and bacteria) ecological model developed for gaining insight into the mechanisms that drive plankton dynamics in a coastal embayment; the Gulf of Gera, Island of Lesvos, Greece. The lack of analytical expressions for the posterior parameter distributions was overcome using Markov chain Monte Carlo simulations; a convenient way to obtain representative samples of parameter values. The Bayesian calibration resulted in realistic reproduction of the key temporal patterns of the system, offered insights into the degree of information the data contain about model inputs, and also allowed the quantification of the dependence structure among the parameter estimates. Finally, our study uses two synthetic datasets to examine the ability of the updated model to provide estimates of predictive uncertainty for water quality variables of environmental management interest.     

Improvement of air quality by means of transportation system management

Under the United States federal Clean Air Act Amendments of 1977, states must implement transportation system management (TSM) tactics in urban areas that have not attained national ambient air quality standards for carbon monoxide and photochemical oxidants. This paper provides a preliminary assessment of the effectiveness and feasibility of using TSM tactics to improve air quality. Based on this assessment, the authors conclude that TSM measures should be effective in eliminating localized carbon monoxide problems, but that such measures are not likely to contribute significantly toward reducing regional oxidant levels. In addition, because most individual TSM tactics can have only marginal impacts on regional motor vehicle emissions, coordinating the planning and implementation of a portfolio of TSM measures will be an essential element of an effective TSM program for improving air quality.