Empirical analysis of transportation investment and economic development at state, county and municipality levels

Numerous studies have found positive correlation between transportation infrastructure investment and economic development. Basically these studies use a conventional production function model augmented by a public capital input, mainly highways, rail and other transportation facilities. While the range of the measured economic growth effects varies widely among studies, the positive elasticity between transportation investment and economic development is now commonly accepted. Still a major puzzling issue is that the magnitude of the measured effect seems to decline significantly as the econometric model is further refined, mainly with regard to space and time lags. That is, the use of national or state data produces elasticity results, which are much larger than when using county or municipality data. Similarly, when we introduce into the econometric model a lag between the times when the transportation investments are made and when the economic benefits transpire, the measured elasticities decline with the size of the lag. Thus, the main objective of this paper is to investigate these issues analytically and empirically and provide a plausible explanation. We do so by using alternative econometric models, applying them to a database, which is composed of longitudinal state, county and municipality observations from 1990 to 2000. The key result is that transportation investments produce strong spillover effects relative to space and time. Unless these factors are properly accounted for many reported empirical results are likely to be overly biased, with important policy implications.     

A bi-criteria indicator to assess supply chain network performance for critical needs under capacity and demand disruptions

In this paper, we develop a supply chain/logistics network model for critical needs in the case of disruptions. The objective is to minimize the total network costs, which are generalized costs that may include the monetary, risk, time, and social costs. The model assumes that disruptions may have an impact on both the network link capacities as well as on the product demands. Two different cases of disruption scenarios are considered. In the first case, we assume that the impacts of the disruptions are mild and that the demands can be met. In the second case, the demands cannot all be satisfied. For these two cases, we propose two individual performance indicators. We then construct a bi-criteria indicator to assess the supply chain network performance for critical needs. An algorithm is described which is applied to solve a spectrum of numerical examples in order to illustrate the new concepts.     

Integrating geographic information systems into transit ridership forecast models

Researchers have produced sophisticated modal split and transit demand models, including forecasts that are sensitive to the level of service. However, little effort has been made to integrate these models into corridor studies and route alignment analyses since (a) re-routing is itself an extremely complex modeling task, and (b) the results of the demand models are presented in tabular form with no facility to visualize spatial patterns and relationships that, if recognized, would aid in the routing tasks. GIS tools can be used, together with the demand models, to identify both clusters of city blocks that house families with certain socioeconomic characteristics and potential trip destinations conducive to transit use. In other words, GIS tools can be used to better measure some of the factors that are needed by transit demand models. The results of these models can be displayed graphically, enabling analysts to target places needing improved service, evaluate route re-alignment alternatives, and operate more efficient and effective bus lines. This paper examines how a particular class of model used by transit agencies for estimating ridership can be integrated with GIS tools in order to facilitate such analyses. It also explores the effects of visualization of routes, demographics, and employment data on the process of designing route alignments with better targeting of high transit ridership areas. This paper is part of a research project sponsored by the Region One University Transportation Center, at MIT.     

The transaction cost approach to modeling the demand for automobiles

The purchase of an automobile involves significant transaction costs in addition to the purchase price. Therefore, the assumptions implied by static car holding models are invalid. This paper describes a dynamic approach to the modeling of level-of-ownership and auto-type choice, based on a transaction choice model which utilizes information on past car ownership. The cost or disutility of a transaction depends on the attributes of the household and the purchased car, as well as on past car-ownership characteristics. A set of assumptions underlying the incorporation of transaction costs in the model is presented. The paper discusses the econometric implications of omitting the dynamic attributes (i.e., past ownership characteristics). A disaggregate model was estimated, using a choice-based sample consisting of a random sample of households enriched with a sample of households which transacted in the car market during the study period. This sampling method combined with a random choice of a subset of the car alternatives provides for a cost-effective method to estimate a transaction model.     

Journey to work and job search characteristics of the urban poor

Gender differences in work trip and job search patterns have received several analytical attention in recent years. A consistent finding in the literature is that women work closer to home than men because of their lower income, greater household responsibilities, and heavier reliance on public transit. While these findings pervade the literature, there has been little analysis into the extent to which they hold in the exclusive case of the urban poor. Can poor women afford to choose between jobs on the basis of journey to work considerations, any more than poor men? Using a survey data from Edmonton, this study examines the gender differences in commuting and job search patterns of the urban poor. The findings suggest that, even among the low income population, women have shorter work trips and greater preference for part-time jobs than men because of their child care and household responsibilities. More women than men did not have enough time for their job search activities; and fewer women than men were prepared to accept job offers in all parts of the study area due to their household responsibilities. The results suggest that while males' employment problems are tied primarily to the working of the labour market, through inadequate skills and lack of good-paying jobs, females' employment problems are more explicable in terms of their role as mothers and homemakers.     

Effect of traffic information on commuters' propensity to change route and departure time

Considerable public and private resources are devoted to the collection and dissemination of real-time traffic information in the Chicago area. Such information is intended to help individuals make more informed travel decisions, yet its effect on behavior remains largely unexplored. This study evaluates the effect of traffic information on travelers' route and departure time changes and provides a stronger basis for developing advanced information systems. Downtown Chicago automobile commuters were surveyed during the AM peak period. The results indicate that a majority of the respondents access, use and respond to information. For example, individuals use travel information to reduce their anxiety—even if they do not change travel decisions; this indicates that information may have “intrinsic” value. That is, simply knowing traffic conditions is valued by travelers. More than 60% of the respondents had used traffic information to modify their travel decisions. Multivariate analysis using the ordered probit model showed that individuals were more likely to use traffic reports for their route changes if they perceived traffic reports to be accurate and timely, and frequently listened to traffic reports. Respondents were more likely to change their departure times if they perceived traffic reports to be accurate and relevant, and frequently listened to traffic reports. The implication for Advanced Traveler Information Systems are that they may be designed to support both enroute and pre-trip decisions. ATIS performance, measured in terms of accuracy, relevance and timeliness would be critical in the success of such systems. Further, near-term prediction of traffic conditions on congested and unreliable routes (where conditions change rapidly) and incident durations is desirable.     

Stated choice: a study in predictive validity using an aggregate truth set

Stated Choice models expand the ability of transportation planners to forecast future trends. The Stated Choice approach can forecast demand for new services or policies. However, Stated Choice models are subject to a range of experimental error not found within Revealed Preference (RP) designs. Primary among the concerns facing researchers is the ability of respondents to understand and operate upon hypothetical choice scenarios in a manner that will reproduce choices made under actual situations. These concerns are specified in the magnitude of a scaling factor. Efforts to estimate the scaling factor has proceeded by linking real decisions taken from a revealed preference survey with comparable decisions made under hypothetical conditions. However, where the alternative is new, actual decision data is not available. This study examines the level of error incorporated in a study where no RP data is available. The test of predictive validity focuses on the switching behavior of commuters at a single employment site. The actual data used to test the forecast is limited to company wide or aggregate ridership levels on the public transit mode taken two years after estimation of the SC model. The Fowkes and Preston hypothesis is examined and shown to bound the future actual value between forecasts derived from probabilistic and deterministic methods. The results show that with the passage of time, the probabilistic method approaches the reported ridership levels within 15 percent error.     

核废料的处理 分离嬗变可以缩短核废料的毒性期

核能在全欧洲能源供应方面居功甚伟。在欧盟25个成员国中，13个国家共有148座核反应堆，产生的总电力达到125GWh，每年可生产电力850TWh，占欧盟总电力需求的35%.     

Socio-ecological Mobility: A Research Strategy for a New Coastline

Abstract

Persistent development, population pressures, and increasing natural hazards are unequivocally changing socio-ecological systems in the coastal zone. This essay provides direction and initiates scientific dialog on the potential role of mobility in adapting to natural and social changes in coastal environments. The essay identifies four key research areas on information needed to develop coastal management actions and policies that support and recognize socio-ecological coupling in coastal areas. The proposed research includes: (1) modeling localized scenarios that illustrate the tradeoffs associated with various sea level rise adaptation, (2) assessing and consolidating mobility terminology for different applications and contexts, (3) developing solutions to synchronize the co-migration of natural environments and built infrastructure, and (4) evaluating existing or creating new transparent, equitable, and sustainable policies and incentives to support socio-ecological mobility by using case studies and social science methods to understand how people make mobility decisions in different contexts.     

Combining web and face-to-face in travel surveys: comparability challenges?

Response rates for household travel surveys are tending to fall, and it seems unlikely that this trend will be reversed in the future. In recent years, travel data collection methods have evolved in order to obtain reliable data that are sufficiently detailed to feed increasingly complex models, and in order to integrate new technologies into survey protocols (Internet, GPS??). Combining different media is an obvious low-cost way of improving data quality as it increases the overall response rate. But the question of the comparability of data over time and between different survey modes remains unresolved. This paper makes a comparative analysis between the travel behaviours of web-based survey respondents and respondents to a face-to-face interview. The data were obtained from the 2006 Lyon conurbation household travel survey. Our analysis shows that the Internet respondents reported fewer trips per day than the face-to-face respondents (3.00 vs. 4.04 daily trips), and that the differences between the two groups varied according to the travel mode and trip purpose. While part of this difference can be explained by socioeconomic disparities (the Internet respondents had a specific profile) we cannot exclude the possibility of under-reporting due to the web medium.