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Mintesnot G. Woldeamanuel Rita Cyganski Angelika Schulz Andreas Justen 《Transportation》2009,36(4):371-387
For economic and environmental policy formulation and with the effort of creating less car dependent societies, it is important
to study the changing characteristics of car ownership in a household through time as well as factors responsible of these
variations. There is a vast body of literature on empirical studies of car ownership and use. These studies have investigated
the socio-economic background of the decision maker, the built environment and the perception associated with owning a car
as determinant factors of car ownership and use. In most cases, these analyses have been carried out using cross-sectional
data sets. However, the analysis of factors determining changes in travel behavior of an individual or household requires
information on their behavior over time (longitudinal data set). In this study, the German Mobility Panel (1996–2006) is used
to examine variation of car ownership through time and across households. The panel data modeling results showed that there
are variations of car ownership between households whereas changes in car ownership of a given household over time (within
household variations) are insignificant. The influence of other factors such as the households’ socio-economic background,
the availability of public transportation and shopping/leisure facilities, perception on parking difficulties and satisfaction
with existing public transportation services on the car owning characteristics of households is also presented and discussed
in this paper.
相似文献
Andreas JustenEmail: |
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本文建立了非定常螺旋桨势函数面元法的理论方法和数值方法,发展了相应的计算机程序,采用通过迭代实现的非线性压力库塔条件,计算了一常规桨和一大侧斜桨的桨叶表面非定压力,并与测试结果及人的计算结果进行了比较。 相似文献
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The production function approach is used to introduce the effect of public infrastructure on economic growth focusing on its spillover effects. We improve the existing literature both from a conceptual and methodological perspective. As regressors we incorporate variables related to the new concepts of internal and imported transport infrastructure capital stocks, which are actually used in commercial flows, calculated by network analysis performed in GIS. The internally used capital stock represents own infrastructure that benefits accessing markets within the region itself, while the imported capital stock captures the spillover effect associated to the use of the infrastructure situated in neighboring regions. From a methodological perspective, we introduce spatial interdependence into these models, applying the most recent spatial econometric techniques based on instrumental variables estimation in spatial autoregressive panel models in comparison with Maximum Likelihood estimation methods. We illustrate the methodology with Spanish provincial panel data for the period 1980–2007. Results support the hypothesis that the imported capital has a positive spillover effect on production. 相似文献
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The maximum approximate composite marginal likelihood (MACML) estimation of multinomial probit-based unordered response choice models 总被引:1,自引:0,他引:1
Chandra R. Bhat 《Transportation Research Part B: Methodological》2011,45(7):923-939
The likelihood functions of multinomial probit (MNP)-based choice models entail the evaluation of analytically-intractable integrals. As a result, such models are usually estimated using maximum simulated likelihood (MSL) techniques. Unfortunately, for many practical situations, the computational cost to ensure good asymptotic MSL estimator properties can be prohibitive and practically infeasible as the number of dimensions of integration rises. In this paper, we introduce a maximum approximate composite marginal likelihood (MACML) estimation approach for MNP models that can be applied using simple optimization software for likelihood estimation. It also represents a conceptually and pedagogically simpler procedure relative to simulation techniques, and has the advantage of substantial computational time efficiency relative to the MSL approach. The paper provides a “blueprint” for the MACML estimation for a wide variety of MNP models. 相似文献
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Erika Spissu Abdul Rawoof Pinjari Chandra R. Bhat Ram M. Pendyala Kay W. Axhausen 《Transportation》2009,36(5):483-510
Activity-travel behavior research has hitherto focused on the modeling and understanding of daily time use and activity patterns
and resulting travel demand. In this particular paper, an analysis and modeling of weekly activity-travel behavior is presented
using a unique multi-week activity-travel behavior data set collected in and around Zurich, Switzerland. The paper focuses
on six categories of discretionary activity participation to understand the determinants of, and the inter-personal and intra-personal
variability in, weekly activity engagement at a detailed level. A panel version of the Mixed Multiple Discrete Continuous
Extreme Value model (MMDCEV) that explicitly accounts for the panel (or repeated-observations) nature of the multi-week activity-travel
behavior data set is developed and estimated on the data set. The model also controls for individual-level unobserved factors
that lead to correlations in activity engagement preferences across different activity types. To our knowledge, this is the
first formulation and application of a panel MMDCEV structure in the econometric literature. The analysis suggests the high
prevalence of intra-personal variability in discretionary activity engagement over a multi-week period along with inter-personal
variability that is typically considered in activity-travel modeling. In addition, the panel MMDCEV model helped identify
the observed socio-economic factors and unobserved individual specific factors that contribute to variability in multi-week
discretionary activity participation.
Erika Spissu is currently a Research Fellow at the University of Cagliari (Italy). She received her Ph.D. from the University of Palermo and University of Cagliari (Italy) in Transport techniques and economics. She spent the past 2 years at the University of Texas at Austin as a Research Scholar focusing primarily in activity-based travel behavior modeling, time use analysis, and travel demand forecasting. Abdul Rawoof Pinjari is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of South Florida, Tampa. His research interests include time-use and travel-behavior analysis, and activity-based approaches to travel-demand forecasting. He has his Ph.D. from the University of Texas at Austin. Chandra R. Bhat is a Professor in Transportation at The University of Texas at Austin. He has contributed toward the development of advanced econometric techniques for travel behavior analysis, in recognition of which he received the 2004 Walter L. Huber Award and the 2005 James Laurie Prize from the American Society of Civil Engineers (ASCE), and the 2008 Wilbur S. Smith Distinguished Transportation Educator Award from the Institute of Transportation Engineers (ITE). He is the immediate past chair of the Transportation Research Board Committee on Transportation Demand Forecasting and the International Association for Travel Behaviour Research. Ram M. Pendyala is a Professor of Transportation Systems in the Department of Civil, Environmental, and Sustainable Engineering at Arizona State University. He teaches and conducts research in travel behavior analysis, travel demand modeling and forecasting, activity-based microsimulation approaches, and time use. He specializes in integrated land use—transport models, transport policy formulation, and public transit planning and design. He is currently the Vice-Chair of the International Association for Travel Behavior Research and is the immediate past chair of the Transportation Research Board Committee on Traveler Behavior and Values. He has his PhD from the University of California at Davis. Kay W. Axhausen is a Professor of Transport Planning at the Swiss Federal Institute of Technology (ETH) Zurich. Prior to his appointment at ETH, he worked at the Leopold Franzens University of Innsbruck, Imperial College London and the University of Oxford. He has been involved in the measurement and modelling of travel behaviour for the last 25 years, contributing especially to the literature on stated preferences, microsimulation of travel behaviour, valuation of travel time and its components, parking behaviour, activity scheduling and travel diary data collection. 相似文献
Kay W. AxhausenEmail: |
Erika Spissu is currently a Research Fellow at the University of Cagliari (Italy). She received her Ph.D. from the University of Palermo and University of Cagliari (Italy) in Transport techniques and economics. She spent the past 2 years at the University of Texas at Austin as a Research Scholar focusing primarily in activity-based travel behavior modeling, time use analysis, and travel demand forecasting. Abdul Rawoof Pinjari is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of South Florida, Tampa. His research interests include time-use and travel-behavior analysis, and activity-based approaches to travel-demand forecasting. He has his Ph.D. from the University of Texas at Austin. Chandra R. Bhat is a Professor in Transportation at The University of Texas at Austin. He has contributed toward the development of advanced econometric techniques for travel behavior analysis, in recognition of which he received the 2004 Walter L. Huber Award and the 2005 James Laurie Prize from the American Society of Civil Engineers (ASCE), and the 2008 Wilbur S. Smith Distinguished Transportation Educator Award from the Institute of Transportation Engineers (ITE). He is the immediate past chair of the Transportation Research Board Committee on Transportation Demand Forecasting and the International Association for Travel Behaviour Research. Ram M. Pendyala is a Professor of Transportation Systems in the Department of Civil, Environmental, and Sustainable Engineering at Arizona State University. He teaches and conducts research in travel behavior analysis, travel demand modeling and forecasting, activity-based microsimulation approaches, and time use. He specializes in integrated land use—transport models, transport policy formulation, and public transit planning and design. He is currently the Vice-Chair of the International Association for Travel Behavior Research and is the immediate past chair of the Transportation Research Board Committee on Traveler Behavior and Values. He has his PhD from the University of California at Davis. Kay W. Axhausen is a Professor of Transport Planning at the Swiss Federal Institute of Technology (ETH) Zurich. Prior to his appointment at ETH, he worked at the Leopold Franzens University of Innsbruck, Imperial College London and the University of Oxford. He has been involved in the measurement and modelling of travel behaviour for the last 25 years, contributing especially to the literature on stated preferences, microsimulation of travel behaviour, valuation of travel time and its components, parking behaviour, activity scheduling and travel diary data collection. 相似文献
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汽车覆盖件成形过程起皱模拟的数值方法 总被引:1,自引:0,他引:1
采用虚功率增率型原理和考虑向剪切变形的Mindlin型曲壳单元,动态界面引入库仑摩擦定律所建立的板材成形弹塑性大变形有限元模型,以Hill关于弹塑性材料唯一性的充分性条件为分叉起皱判据,成功地模拟了方盒拉深成形凸缘起皱现象及圆锥件拉深成形侧壁起皱现象。 相似文献
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以中国11 条物流通道为实证对象,综合测算物流通道技术水平,构造基于地理距 离的空间邻接权重矩阵,检验相关变量的空间自相关性,构建空间杜宾面板数据模型验证了 中国物流通道的空间溢出效应.研究表明:中国物流通道总体上具有显著的正向空间溢出效 应,但从分布于不同空间的物流通道看,长江、沿海、京九、陇海兰新和沪昆物流通道正向空间 溢出效应显著;而京沪、京广和宝昆物流通道研究期内空间溢出效应不显著.我国物流通道的 空间溢出效应具有显著的空间差异,应因地制宜地合理化建设物流通道. 相似文献