Community Perceptions of a World Heritage Nomination Process: The Ningaloo Coast Region of Western Australia

The remote Ningaloo Coast region, the location of Australia's largest fringing coral reef, was designated as World Heritage (WH) in 2011 based on its outstanding natural values. In the past, the WH nomination process predominantly involved experts and state officials. More recently, local community involvement has become a required part of the process, representing a move toward participatory governance that can potentially influence WH designation. Understanding community perceptions of the WH nomination process provides insights into the consequences of community involvement. Interviews were conducted with key local community members involved in the Ningaloo Coast WH nomination. Interviews focused on the perceptions and experience of the nomination process and local meanings of WH designation. Results indicated that while there was support for WH designation, the nomination process was seen as controversial. Community involvement was dominated by local political and social concerns, mistrust, misinformation, and perceived unfairness. Concerns were influenced by past and current government actions and decision-making in the region. The article identifies some challenges associated with local community involvement in a WH nomination process. These challenges raise questions about participatory governance and how local community's engage in the WH nomination process for coastal regions identified by experts as globally significant.     

Travel differences by gender for older people in London

As a guarantee of life quality, older people’s travel demand has to be satisfied, so understanding their travel demand is important. An important point to bear in mind is that older people are not a homogeneous group but that distinguishing between older women and older men in their mobility needs and travel patterns is necessary. Older people’s travel demand needs to be investigated from many different aspects, including trip generation, travel time, and mode choice. In this study, the investigation is focused on older people’s trip chaining, including trip chain complexity, tour composition in a chain.     

A methodology to estimate the revenue anticipated from State-level alternative financing approaches in the US

A major issue that State Departments of Transportation (DOTs) in the US face relates to financing future transportation investments. Questions of interest to State DOT officials relate to the suitability and revenue potential of alternative financing approaches. This paper presents a methodology to estimate the potential levels of revenue associated with the use of selected combinations of financing approaches and to assess the adequacy of these revenues vis-a-vis various levels of investments being considered by decision-makers. The methodology is designed to accommodate a wide array of inputs such as major policy objectives and initial assumptions that may vary significantly from State to State in order to provide a greater flexibility of implementation. The application of this methodology is demonstrated with an illustrative example for Massachusetts. This paper should be of interest to State DOTs seeking an acceptable combination of financing approaches to support future transportation investments.     

Creating synthetic baseline populations

To develop activity-based travel models using microsimulation, individual travelers and households must be considered. Methods for creating baseline synthetic populations of households and persons using 1990 census data are given. Summary tables from the Census Bureau STF-3A are used in conjunction with the Public Use Microdata Sample (PUMS), and Iterative Proportional Fitting (IPF) is applied to estimate the proportion of households in a block group or census tract with a desired combination of demographics. Households are generated by selection of households from the associated PUMS according to these proportions. The tables of demographic proportions which are exploited here to make household selections from the PUMS may be used in traditional modeling. The procedures are validated by creating pseudo census tracts from PUMS samples and considering the joint distribution of the size of households and the number of vehicles in the households. It is shown that the joint distributions created by these methods do not differ substantially from the true values. Additionally the effects of small changes in the procedure, such as imputation of additional demographics and adding partial counts to the constructed demographic tables are discussed in the paper.     

WTO与交通企业发展

刘光溪:入世谈判过程本身具有重大意义 入世谈判的过程对于中国经济的发展、中国经济体制改革的深化是一个巨大的教育过程.这次谈判不光是经济和贸易的交锋,还是两种文化、两种理念的碰撞,对中华民族价值取向、理性思维将产生深远的影响.     

On the structure of weekly activity/travel patterns

Understanding the process of activity scheduling is a critical pre-requisite to an understanding of changes in travel behavior. To examine this process, a computerized survey instrument was developed to collect household activity scheduling data. The instrument is unique in that it records the evolution of activity schedules from intentions to final outcomes for a weekly period. This paper summarizes an investigation of the structure of activity/travel patterns based on data collected from a pilot study of the instrument. The term “structure” refers to the sequence by which various activities enter one’s daily activity scheduling process. Results of the empirical analyses show that activities of shorter duration were more likely to be opportunistically inserted in a schedule already anchored by their longer duration counterparts. Additionally, analysis of travel patterns reveals that many trip-chains were formed opportunistically. Travel time required to reach an activity was positively related to the scheduling horizon for the activity, with more distant stops being planned earlier than closer locations.     

A sequential approach to exploiting the combined strengths of SP and RP data: Application to freight shipper choice

The possibility of and procedure for pooling RP and SP data have been discussed in recent research work. In that literature, the RP data has been viewed as the yardstick against which the SP data must be compared. In this paper we take a fresh look at the two data types. Based on the peculiar strengths and weaknesses of each we propose a new, sequential approach to exploiting the strengths and avoiding the weaknesses of each data source. This approach is based on the premise that SP data, characterized by a well-conditioned design matrix and a less constrained decision environment than the real world, is able to capture respondents' tradeoffs more robustly than is possible in RP data. (This, in turn, results in more robust estimates of share changes due to changes in independent variables.) The RP data, however, represent the current market situation better than the SP data, hence should be used to establish the aggregate equilibrium level represented by the final model. The approachfixes the RP parameters for independent variables at the estimated SP parameters but uses the RP data to establish alternative-specific constants. Simultaneously, the RP data are rescaled to correct for error-in-variables problems in the RP design matrixvis-à- vis the SP design matrix. All specifications tested are Multinomial Logit (MNL) models.The approach is tested with freight shippers' choice of carrier in three major North American cities. It is shown that the proposed sequential approach to using SP and RP data has the same or better predictive power as the model calibrated solely on the RP data (which is the best possible model for that data, in terms of goodness-of-fit figures of merit), when measured in terms of Pearson's Chi-squared ratio and the percent correctly predicted statistic. The sequential approach is also shown to produce predictions with lower error than produced by the more usual method of pooling the RP and SP data.     

Bayesian statistical data assimilation for ecosystem models using Markov Chain Monte Carlo

This study considers advanced statistical approaches for sequential data assimilation. These are explored in the context of nowcasting and forecasting using nonlinear differential equation based marine ecosystem models assimilating sparse and noisy non-Gaussian multivariate observations. The statistical framework uses a state space model with the goal of estimating the time evolving probability distribution of the ecosystem state. Assimilation of observations relies on stochastic dynamic prediction and Bayesian principles. In this study, a new sequential data assimilation approach is introduced based on Markov Chain Monte Carlo (MCMC). The ecosystem state is represented by an ensemble, or sample, from which distributional properties, or summary statistical measures, can be derived. The Metropolis-Hastings based MCMC approach is compared and contrasted with two other sequential data assimilation approaches: sequential importance resampling, and the (approximate) ensemble Kalman filter (including computational comparisons). A simple illustrative application is provided based on a 0-D nonlinear plankton ecosystem model with multivariate non-Gaussian observations of the ecosystem state from a coastal ocean observatory. The MCMC approach is shown to be straightforward to implement and to effectively characterize the non-Gaussian ecosystem state in both nowcast and forecast experiments. Results are reported which illustrate how non-Gaussian information originates, and how it can be used to characterize ecosystem properties.     

How much disruption to activities could fuel shortages cause? – The British fuel crisis of September 2000

In September of 2000 the UK experienced a blockade of oil refineries in response to rising fuel prices. These protests resulted in severe fuel supply disruptions that intensified over the course of about one week. During the peak of the crisis, travel activity by car was curtailed. This paper analyzes survey data collected about two months after the crisis utilizing the recent memory of respondents as to how they would expect this sort of disruption to affect their participation in daily activities. Specifically, we focused on a variety of non-discretionary and discretionary activities and examined what factors are associated with respondents expecting disruption to those activities. Statistical models were developed to analyze how demographic factors, commute mode selection, vehicle characteristics, and various other factors can explain how individuals expect disruption to their activities. Results suggest that the majority of individuals do not expect major disruptions, although for more car-dependent individuals, disruption was expected to be substantial, especially for work-related trips. These results have implications for the potential success and benefits of an integrated transport policy.     

UK tonnage tax: subsidy or special case?

Following the introduction of tonnage tax for UK-based shipping companies in 2000, the industry now has the opportunity to opt for a tax regime that is beneficial in contrast to the corporation tax applied to most other sectors. This paper aims to summarize the tonnage tax scheme and then to go on to assess whether its introduction was appropriate. In doing so, it assesses whether the benefits it brings to the UK shipping industry are in fact fiscally justifiable in terms of the advantages that have been suggested recently by a number of commentators. These are claimed to derive from the comparative advantage of the UK shipping industry, the need for more skilled on-shore shipping staff with sea-going experience, and in terms of sustaining the maritime cluster typified by the maritime activities of the City of London.