Exploring the effects of the rural built environment on household car ownership after controlling for preference and attitude: Evidence from Sichuan,China

With the rapid infrastructure development and economic growth in China, household car ownership in the country's rural areas has changed dramatically in the past 16 years. The total number of cars owned by households in rural areas is currently 12 times higher than it was 16 years ago. The exploration of the effects of the built environment on household car ownership in China's rural areas is worthwhile. However, few studies have investigated this topic. To fill in the research gap, this work collected 374 household data from rural areas in China to examine the effects of the built environment in Sichuan's rural areas on the number of cars in a household. It considered family structure, socioeconomic characteristics, and individual's perceptions of the built environment, preferences towards the built environment and attitudes towards car ownership (shortened to perceptions, preferences and attitudes from now on). Geographic information system (GIS) technology, combined with on-site measurement, was used for data collection. The multinomial logit model was applied for estimation. Household structure and the built environment (including the perceived built environment and the objective built environment) significantly influence the number of cars in a household. By contrast, preference and attitude attributes have less influence on car ownership. Most of the findings are in line with the literature in the context of Chinese cities. Nevertheless, new results are also found. For example, rural hukou, and building density have significant positive impacts on household car ownership in China's rural areas, which is in contrast with their effects on cities. As the first study on rural areas in China, this research provides some insights for rural planners and policymakers to understand better the relationship between built environment and household car ownership.     

The influence of stratification by motor-vehicle ownership on the impact of built environment factors in Indian cities

Development of compact cities, many contend, aids in the promotion of sustainable modes (public transit, walking and cycling). But the studies done until now have inadequately represented the effect of socio-economic stratification on the relationship between built environment factors and non-motorized transport (NMT) mode choice, which is important in context of a developing country like India. The present study, done in the city of Bangalore, analyzes the influence of built environment factors –density and diversity - on the mode choice and trip distance for the two segments: respondents owning at least one personal vehicle and respondents not owning any personal vehicle. The built environment factors are analyzed for their marginal effects in the presence of various socio-demographic and alternate specific attributes. The results of the built environment factors for the vehicle non-owning group highlighted the requirement of a policy framework to reduce their trip distance by controlling their employment and housing location. The gender of a commuter had a significant effect on the choice of modes, and the results that females had a higher likelihood of using NMT compared with males contradicted the results in other cities. Also, the trip distance model determined that females preferred a shorter walking distance compared with males. Further, the study determined the need for a well-planned, inclusive and coordinated land-use and transport control strategies in the future.     

Millennials,built form,and travel insights from a nationwide typology of U.S. neighborhoods

We examine the relationship between the built environment and the travel of Millennials in the United States. We develop a neighborhood typology to characterize the built environment and transportation networks in almost every U.S. census tract, allowing us to identify possible synergistic and/or threshold effects on travel. We measure travel behavior in two ways: (1) using a multi-faceted traveler typology created using latent class analysis, and (2) by measuring the vehicle miles of travel among people in each of these traveler types. This dual approach allows us to distinguish between the built environment changes needed to encourage travel by modes other than driving, and those needed to reduce vehicle miles traveled among drivers. Using a multinomial logistic regression, we find that travel patterns are relatively stable along much of the urban-rural continuum, everything else equal. Driving was substantially lower only in “Old Urban” neighborhoods, where densities, job access, and transit service are dramatically higher than in all other neighborhood types. This finding implies that dramatic changes in the built environment—doubling or even tripling development density or transit service—may do little to get young people out of their cars when initial densities or transit services are low, as they are in most of the U.S. Conversely, reducing vehicle miles traveled among drivers appears to require more modest built form changes, a finding that offers some room for optimism among those concerned with auto dependence.     

Occupancy,oil prices,and stock returns: Evidence from the U.S. airline industry

This paper examines whether occupancy of seats affects stock returns of airline companies and how this relationship is affected by WTI oil prices. Our approach combines revenues (occupancy) and costs (oil prices) for 33 U.S. airline companies from 1990 to 2019. Using travel capacity utilization data from U.S. carriers at monthly frequency and exploiting fixed-effects regression models, we document a positive relation between occupancy and stock returns, which is attenuated by oil prices. The role of oil becomes larger with asymmetries: the effects of oil prices are higher when moving up than down. Airline stocks always respond by more than the overall stock market.     

Airport ownership and financial performance: Evidence from Italy

In the past few decades many countries have increased the presence of various forms of private sector involvement in airport ownership and management. This paper focuses on the financial performance of Italian airport companies. We present empirical evidence separately for two groups where public or private management majority prevails. The main findings indicate that companies with a private majority outperform the others in terms of financial indicators that are related to operating income.     

The U.S. Airways Group: A post-merger analysis

America West Airlines acquired the bankrupt US Airways on September 27, 2005 to form the US Airways Group, improving its competitive position in the US airline industry. This paper analyzes the post-merger performance of the US Airways Group using airline operating metrics and financial ratios for the period 2005 to 2013. While the airline has still a long way to go to improve its leverage and liquidity ratios, its capital structure and ability to pay its obligations have improved since 2005. Moreover, although the airline is still inefficient in utilizing its assets, the efficiency improvements achieved since the merger have resulted in profits and positive returns to investors. Its share prices have also largely outperformed the S&P 500 and the XAL since the merger, an indication that investors are pleased with how the merger is developing over time. In view of the US Airways Group's improving financial and operating performance, the merger is, essentially, a success.     

Association between the built environment and children's independent mobility: A meta-analytic review

Children's independent mobility (CIM) is considered as a determining criterion of child-friendly built environment (BE). Researchers have made a substantial effort to identify the characteristics of the BE that affect CIM and thereby to inform city policy to promote CIM. Although the findings from these studies are useful to inform context specific CIM policy, together they provide inconclusive results. This study made a first attempt to draw a generalised conclusion through a meta-analysis of existing knowledge base. The analysis was conducted using primary studies reporting 13 BE-CIM links and published between 1980 and 2016. Overall effect size (ES), directions, and consistency of each link were calculated, also stratified by contexts, using the reported results from the primary studies and based on a random effect model. The results show that four BE factors (dead-end street, % of residential land, % of commercial land, and residential location type) have a positive association with CIM; traffic volume has a neutral association; and the remaining eight factors (vehicular street width, road density, intersection density, major road proportion, land use mix, availability of recreational facilities, residential density, and distance to destination) have a negative association. Living in a dead end street was found to have the strongest positive ES (0.352), with moderate level of consistency across the primary studies. In contrast, land use mix has the strongest negative ES (− 0.212) but with the highest level of inconsistency. Both ESs and consistencies, however, vary between developing and developed country contexts. Diversity in contexts, research design, and measurement instruments across the primary studies contributed to the heterogeneous results. The findings of this research serve as a guide for practitioners and researcher alike to make an informed decision about the BE factors that consistently foster or hinder CIM in different contexts.     

美国铁路管制的由来和发展：历史和思路

回顾并评析1887年以来的美国铁路管制历史,认为美国铁路放权改革经验值得总结。     

The geography of air freight: connections to U.S. metropolitan economies

Despite the rapid growth of air freight shipments, much of the existing literature on the geography of air transportation has paid more attention to passenger travel than air freight. The purpose of this paper is to elevate our understanding of air freight by determining which specific variables most influence and shape the geographic distribution of air freight by metropolitan area using stepwise regression analysis. The empirical results suggest a regression model of five independent variables was the most parsimonious solution where the final model accounted for 71.1% of the variation in air freight shipments by metropolitan area (MA). The most important predictor was the traffic shadow effect, where less populated MAs under the traffic shadow of larger MAs tended to generate lower levels of freight. The model also suggested that other key predictors included the employment market share in transportation-shipping-logistics industries, per capita personal income, the number of medical diagnostic and supplier establishments, and above average wages in high technology. Overall, metropolitan markets with diverse and efficient ground support systems, freight forwarders and other transportation services, a more affluent population, an intense agglomeration of medical laboratories and related suppliers, and a well paid skilled workforce engaged in computer systems design and electronic product manufacturing are more likely to ship freight by air.     

An examination of the factors that impact upon multiple vehicle ownership: The case of Dublin, Ireland

This paper examines the characteristics of households with multiple car ownership in Dublin, Ireland. Data from the 2006 Census of Ireland are analysed to ascertain the characteristics of these households. The analysis of multiple car ownership presented herein examines individual specific, transport availability, and household characteristics to provide an indication of the individuals most likely to have access to more than one vehicle. Understanding the characteristics of households with more than one car is important for many reasons, such as how policies for emissions reductions or pricing regimes might affect households. Ireland, like many countries, has recently launched a number of electric vehicle and car sharing schemes. Traditionally these schemes have been aimed at reducing multiple car ownership, therefore it is important to develop an understanding of the households that would most likely give up an extra car and use a car sharing scheme or an electric vehicle. Also from a sustainability point of view, greater levels of car ownership can result in unsustainable transport patterns.This paper examines the Census data using a multinomial logit regression model to determine the relationships between multiple car ownership levels and several household characteristics. The findings of the paper demonstrate that occupation, public transport availability and residential density all have an impact upon the decision to own more than one vehicle.     

美国保险业的发展状况及未来展望

美国是世界上保险业最发达的国家之一 ,拥有全球最大的保险市场。保险业在美国经济社会发展中发挥着巨大作用。美国保险市场呈垄断竞争格局 ,创新活动十分活跃。美国的保险监管主要由各州负责 ,并以偿付能力监管为重点。为促进保险业的发展 ,美国政府给予了一系列政策支持。未来若干年 ,美国保险业将在跌宕的环境变化中谋求进一步的发展 ,并继续在世界上保持领先地位。     

The indirect effect of the built environment on travel mode choice: A focus on recent movers

Many studies have demonstrated that the built environment has a strong impact on people's travel mode choice. However, the built environment also influences elements such as travel distance and car ownership, which might be the true predictors of which travel modes are chosen. In this study, we analyse the effects of changes in residential neighbourhood on changes in travel mode (for commute trips and leisure trips), both directly and indirectly through changes in car ownership, travel distances and travel attitudes. This study applies a structural equation modelling approach using quasi-longitudinal data from 1650 recently relocated residents in the city of Ghent, Belgium. Results indicate that the built environment has strong direct effects on active leisure trips and car use. However, distance (for car use) and attitudes (for active travel) were found to be important mediating variables. In sum, the effect of the built environment on travel mode choice might be more complex than commonly assumed as it partly seems mediated by travel distance and travel attitudes.     

A methodology for prioritising HSR corridors: from U.S. theory to Spanish practice

The assessment of methodologies to prioritise the construction of new high-speed rail (HSR) corridors has recently become a key issue for transport planners in countries like the U.S., where HSR does not exist. In a climate of financial instability since the onset of the global crisis of 2007–2008, support for new projects is being eroded by serious concerns over the extremely steep costs of high-speed rail, and there is a need for the scientific clarification of the procedure for prioritizing construction.In 2009 a new ranking methodology was developed and applied to 30,000 city pairs in the U.S. to determine their suitability for high-speed rail investment. The existing literature on ranking tools for prioritising HSR corridors is practically non-existent, and, as none of these U.S. lines has been built or put into in operation, this methodology has not been validated. The main aim of this paper is to contribute to these ranking models and highlight their importance in the HSR planning process. The preliminary ranking tool described in this work has been validated using data from the current HSR Spanish network. The results confirm the consistency of the model as a first approach to ranking pairs, mainly for the top O–D relations; however the model has some drawbacks chiefly due to the type of variables used, and their assigned weightings. Finally, some specific improvements are proposed for this ranking approach in order to provide policymakers with a useful tool when planning the construction of new HSR networks.     

Causes and effects between attitudes,the built environment and car kilometres: A longitudinal analysis

Travel-related attitudes are believed to affect the connections between the built environment and travel behaviour. Previous studies found supporting evidence for the residential self-selection hypothesis which suggests that the impact of the built environment on travel behaviour could be overestimated when attitudes are not accounted for. However, this hypothesis is under scrutiny as the reverse causality hypothesis, which implies a reverse direction of influence from the built environment towards attitudes, is receiving increased attention in recent research. This study tests both directions of influence by means of cross-sectional and longitudinal structural equation models. GPS tracking is used to assess changes in travel behaviour in terms of car kilometres travelled. The outcomes show stronger reverse causality effects than residential self-selection effects and that land-use policies significantly reduce car kilometres travelled. Moreover, the longitudinal models show that the built environment characteristics provide a better explanation for changes in car kilometres travelled than the travel-related attitudes. This contradicts the cross-sectional analysis where associations between car kilometres travelled and travel-related attitudes were stronger. This highlights the need for more longitudinal studies in this field.     

The determinants of aeronautical charges of U.S. airports: A spatial analysis

Using U.S. airport data from 2009 through 2016, this study examines the determinants of aeronautical charges of large and medium hub airports and accounts for the spatial dependence of neighboring airports in a spatial panel regression model. Our results show that U.S. airports' aeronautical charges are spatially dependent, and neighboring airport charges are positively correlated, implying that U.S. airports are in price competition with each other even though they are government-owned infrastructure. Additionally, we find evidence of airport cost recovery through non-aeronautical revenues. This may be indicative of the airport's cross-subsidizing aeronautical operations with non-aeronautical revenues. In addition, we found the airports that share revenues with airlines charge lower aeronautical fees than those that do not share revenues. We also found that more congested airports charge higher aeronautical fees.     

Hedging jet fuel price risk: The case of U.S. passenger airlines

Jet fuel accounts for a large portion of passenger airlines' operating costs, and airlines' earnings are susceptible to swings in the price of jet fuel. This study uses daily data over the past two decades to determine the minimum variance hedge ratio for airlines wishing to hedge jet fuel price risk with futures, while also establishing the best cross hedging asset. Airlines hedging with futures would create the most effective hedge by using heating oil futures contracts with a 3-month maturity. We also find that beyond the 3-month veil, increased time to maturity makes heating oil less effective as a cross hedge proxy for jet fuel. However, both in-sample analysis and Monte Carlo simulation results with daily data show that none of the 4 cross hedge proxies, including heating oil, can be considered highly effective.     

Airport security and screening satisfaction: A case study of U.S.

The study analyzes the perception of airport safety by travelers, and how it is related to satisfaction with passenger screening experiences and the perception of public transit safety. It uses the Omnibus Household Survey data collected by the U.S. Bureau of Transportation Statistics and estimates a structural equations model. It finds a positive relationship between Screening Satisfaction and Screening Safety and a positive relationship between the perception of Public Transit Safety and Screening Safety. A lack of experience with using public transit is also found to contribute to travelers perceiving lower levels of Screening Safety at airports, and females compared to males perceive a lower level of Screening Safety. Finally, the study finds causality from a traveler’s satisfaction with the screening process to safety perception.     

The impact of the COVID-19 pandemic on people's mobility: A longitudinal study of the U.S. from March to September of 2020

This paper examines changes in people's mobility over a 7-month period (from March 1st to September 30th, 2020) during the COVID-19 pandemic in the U.S. using longitudinal models and county-level mobility data obtained from people's anonymized mobile phone signals. It differentiates two distinct waves of the study period: Wave 1 (March–June) and Wave 2 (June–September). It also analyzes the relationships of these mobility changes with various social, spatial, policy, and political factors. The results indicate that mobility changes in Wave 1 have a V-shaped trend: people's mobility first declined at the early stage of the COVID-19 pandemic (March–April) but quickly recovered to the pre-pandemic mobility levels from April to June. The rates of mobility changes during this period are significantly associated with most of our key variables, including political partisanship, poverty level, and the strictness of mobility restriction policies. For Wave 2, there was very little mobility decline despite the existence of mobility restriction policies and the COVID-19 pandemic becoming more severe. Our findings suggest that restricting people's mobility to control the pandemic may be effective only for a short period, especially in liberal democratic societies. Further, since poor people (who are mostly essential workers) kept traveling during the pandemic, health authorities should pay special attention to these people by implementing policies to mitigate their high COVID-19 exposure risk.     

Examining the influence of stop level infrastructure and built environment on bus ridership in Montreal

We studied transit ridership from the perspective of the transit provider, with the objective of quantifying the influence of transit system operational attributes, transportation system infrastructure attributes and built environment attributes on the disaggregate stop level boardings and alightings by time of day for the bus transit system in the Montreal region. A Composite Marginal Likelihood (CML) based ordered response probit (ORP) model, that simultaneously allows us to incorporate the influence of exogenous variables and potential correlations between boardings and alightings across multiple time periods of the day is employed. Our results indicate that headway affects ridership negatively, while the presence of public transportation around the stop has a positive and significant effect. Moreover, parks, commercial enterprises, and residential area, amongst others, have various effects across the day on boardings and alightings at bus stops. An elasticity analysis provides useful insights. Specifically, we observe that the most effective way to increase ridership is to increase public transport service and accessibility, whereas enhancements to land use have a smaller effect on ridership. The framework from our analysis provides transit agencies a mechanism to study the influence of transit accessibility, transit connectivity, transit schedule alterations (to increase/reduce headway), and land-use pattern changes on ridership.     

Comparison of major air freight network hubs in the U.S. and China

The increase in global economic connectivity spurred by ties between Chinese manufacturing and a global market, particularly in high value low weight goods, pushed establishment of air cargo networks. These remain under-examined but impactful particularly for second and third tier metropolitan hub cities. This research looks at the air freight connections within China, a major rapidly developing trade center, and use of the aerotropolis concept to accelerate growth in the lagging inland region. References are made to FedEx and UPS networks within their U.S. headquarter region and in China to note differences in political economic contexts and China’s adaptation of developed world models. The theoretical framework includes global production networks strategically coupled by transport logistics linked to aerotropolis type development. Data comes from government aviation and transportation sources, research analyses, corporate and industry reports, and interviews with Chinese officials. Focus falls particularly on Zhengzhou, capital of Henan Province in central China and the country’s first airport-centered economic zone. The conclusion finds that Chinese hub cities more closely correspond to major manufacturing and population centers and central policy directives for development dispersion.