Academic literature on the topic 'Travel Mode Choice'

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Journal articles on the topic "Travel Mode Choice"

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Bamberg, Sebastian, and Peter Schmidt. "CHANGING TRAVEL-MODE CHOICE AS RATIONAL CHOICE:." Rationality and Society 10, no. 2 (1998): 223–52. http://dx.doi.org/10.1177/104346398010002005.

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Matthies, Ellen, Silke Kuhn, and Christian A. Klöckner. "Travel Mode Choice of Women." Environment and Behavior 34, no. 2 (2002): 163–77. http://dx.doi.org/10.1177/0013916502034002001.

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Cheng, Long, Xuewu Chen, Ming Wei, Jingxian Wu, and Xianyao Hou. "Modeling Mode Choice Behavior Incorporating Household and Individual Sociodemographics and Travel Attributes Based on Rough Sets Theory." Computational Intelligence and Neuroscience 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/560919.

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Most traditional mode choice models are based on the principle of random utility maximization derived from econometric theory. Alternatively, mode choice modeling can be regarded as a pattern recognition problem reflected from the explanatory variables of determining the choices between alternatives. The paper applies the knowledge discovery technique of rough sets theory to model travel mode choices incorporating household and individual sociodemographics and travel information, and to identify the significance of each attribute. The study uses the detailed travel diary survey data of Changxi
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Sidharthan, Raghuprasad, Chandra R. Bhat, Ram M. Pendyala, and Konstadinos G. Goulias. "Model for Children's School Travel Mode Choice." Transportation Research Record: Journal of the Transportation Research Board 2213, no. 1 (2011): 78–86. http://dx.doi.org/10.3141/2213-11.

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Wu, Chaoqun, Yulong Pei, and Jingpeng Gao. "Evolution Game Model of Travel Mode Choice in Metropolitan." Discrete Dynamics in Nature and Society 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/638972.

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The paper describes an evolution game model of travel mode choice to determine whether transportation policies would have the desired effect. The model is first expressed as a two-stage sequential game in the extensive form based on the similarity between evolution game theory and the travel mode choice process. Second, backward induction is used to solve for Nash equilibrium of the game based on the Folk Theorem. Third, the sensitivity analysis suggests that a payoff reduction of travel by any mode will result in a rising proportion of inhabitants travelling by that mode and falling proportio
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Hagberg, Johan, and Ulrika Holmberg. "Travel modes in grocery shopping." International Journal of Retail & Distribution Management 45, no. 9 (2017): 991–1010. http://dx.doi.org/10.1108/ijrdm-08-2016-0134.

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Purpose Although the movement of goods by consumers represents a large proportion of the economic and environmental impact of the distribution chain, this topic has been insufficiently explored in the retailing literature. The purpose of this paper is to contribute to the understanding of shopping travel-mode choice in the context of grocery shopping. Design/methodology/approach The paper presents findings from a Swedish national survey of 1,694 respondents that included questions regarding travel-mode choices and consumer characteristics, mobility conditions, shopping behaviours and environme
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Wang, Yanli, Bing Wu, Zhi Dong, and Xin Ye. "A Joint Modeling Analysis of Passengers’ Intercity Travel Destination and Mode Choices in Yangtze River Delta Megaregion of China." Mathematical Problems in Engineering 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/5293210.

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Joint destination-mode travel choice models are developed for intercity long-distance travel among sixteen cities in Yangtze River Delta Megaregion of China. The model is developed for all the trips in the sample and also by two different trip purposes, work-related business and personal business trips, to accommodate different time values and attraction factors. A nested logit modeling framework is applied to model trip destination and mode choices in two different levels, where the lower level is a mode choice model and the upper level is a destination choice model. The utility values from v
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Chen, Hong, Zuo-xian Gan, and Yu-ting He. "Choice Model and Influencing Factor Analysis of Travel Mode for Migrant Workers: Case Study in Xi’an, China." Discrete Dynamics in Nature and Society 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/236216.

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Based on the basic theory and methods of disaggregate choice model, the influencing factors in travel mode choice for migrant workers are analyzed, according to 1366 data samples of Xi’an migrant workers. Walking, bus, subway, and taxi are taken as the alternative parts of travel modes for migrant workers, and a multinomial logit (MNL) model of travel mode for migrant workers is set up. The validity of the model is verified by the hit rate, and the hit rates of four travel modes are all greater than 80%. Finally, the influence of different factors affecting the choice of travel mode is analyze
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Miller, Eric J., Matthew J. Roorda, and Juan Antonio Carrasco. "A tour-based model of travel mode choice." Transportation 32, no. 4 (2005): 399–422. http://dx.doi.org/10.1007/s11116-004-7962-3.

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Li, Ming, Guohua Song, Ying Cheng, and Lei Yu. "Identification of Prior Factors Influencing the Mode Choice of Short Distance Travel." Discrete Dynamics in Nature and Society 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/795176.

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Short distance trips are defined as any trips shorter than or equal to 5 kilometers, which have been found to be a big contributor to the traffic congestion problem. This paper is intended to analyze factors that influence the mode choice of short distance travels in order to help reduce short distance trips by cars. A survey is conducted at two typical kinds of residential areas, one with a high proportion of short distance car trips and another one with a low proportion. Then, by applying the structural equation modeling, it is found that the age, the household income, and the vehicle owners
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Dissertations / Theses on the topic "Travel Mode Choice"

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Pedersen, Tore. "Affective Forecasting in Travel Mode Choice." Doctoral thesis, Karlstads universitet, Avdelningen för psykologi, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-8685.

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The general aim of this thesis was to investigate affective forecasting in the context of public transport. Paper I, Study 1 revealed that non-users of public transport were less satisfied with the services than users. It was hypothesised that non-users were biased in their satisfaction ratings, a claim that was subsequently investigated in Paper I, Study 2, where a field experiment revealed that car users suffer from an impact bias, due to being more satisfied with the services after a trial period than they predicted they would be. To address the question of whether a focusing illusion is th
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Shaw, Shih-lung 1958. "A constrained attitudinal model of urban travel mode-choice behavior /." The Ohio State University, 1987. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487267546982637.

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Reid, John Campbell. "The social psychology of rural travel mode choice." Thesis, University of Sheffield, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.445125.

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Adkins, Arlie Steven. "Determinants of Recent Mover Non-work Travel Mode Choice." PDXScholar, 2014. https://pdxscholar.library.pdx.edu/open_access_etds/1919.

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Active transportation modes of walking and bicycling have the potential to help mitigate environmental and health concerns ranging from growing greenhouse gas emissions to increasing rates of obesity. This dissertation investigates how new movers make decisions about active transportation, particularly non-work utilitarian walking, in the context of a new home and neighborhood. New movers are an important, yet often overlooked, population in travel behavior research because they provide an opportunity to observe behavior adoption in new contexts, but also because the roughly one-in-ten America
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Singleton, Patrick Allen. "Exploring the Positive Utility of Travel and Mode Choice." PDXScholar, 2017. https://pdxscholar.library.pdx.edu/open_access_etds/3780.

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Why do people travel? Underlying most travel behavior research is the derived-demand paradigm of travel analysis, which assumes that travel demand is derived from the demand for spatially separated activities, traveling is a means to an end (reaching destinations), and travel time is a disutility to be minimized. In contrast, the "positive utility of travel" (PUT) concept suggests that travel may not be inherently disliked and could instead provide benefits or be motivated by desires for travel-based multitasking, positive emotions, or fulfillment. The PUT idea assembles several concepts relev
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Broach, Joseph. "Travel Mode Choice Framework Incorporating Realistic Bike and Walk Routes." PDXScholar, 2016. https://pdxscholar.library.pdx.edu/open_access_etds/2702.

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For a number of reasons--congestion, public health, greenhouse gas emissions, energy use, demographic shifts, and community livability to name a few--the importance of walking and bicycling as transportation options will only continue to increase. Currently, policy interest and infrastructure funding for nonmotorized modes far outstrip our ability to model bike and walk travel. To ensure scarce resources are used most effectively, accurate models sensitive to key policy variables are needed to support long-range planning and project evaluation, and to continue adding to our growing understandi
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Wall, Rob. "Psychological and contextual influences on travel mode choice for commuting." Thesis, De Montfort University, 2006. http://hdl.handle.net/2086/13248.

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Travel behaviour - especially car use - is of concern because it contributes to environmental problems such as climate change. Focusing on commuting, this thesis aimed to explain people's travel mode decisions and what might motivate drivers to switch modes. The literature shows that - as in the wider field of environmentallysignificant behaviour - Schwartz's norm-activation theory (NAT) and Ajzen's theory of planned behaviour (TPB) are predominant in travel psychology. Research undertaken for this thesis was based on these theories. Study 1 used logistic regression (n = 312) to test NAT and t
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Tringides, Constantinos A. "Alternative formulations of joint model systems of departure time choice and mode choice for non-work trips." [Tampa, Fla.] : University of South Florida, 2004. http://purl.fcla.edu/fcla/etd/SFE0000240.

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Bouscasse, Hélène. "Essays on travel mode choice modeling : a discrete choice approach of the interactions between economic and behavioral theories." Thesis, Lyon, 2017. http://www.theses.fr/2017LYSE2106/document.

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Cette thèse a pour objectif d’incorporer des éléments de théories de psychologie et d’économie comportementale dans des modèles de choix discret afin d’améliorer la compréhension du choix modal réalisé à l’échelle régionale. Les estimations se basent sur une enquête de type choice experiment présentée en première partie. Une deuxième partie s’intéresse à l’incorporation de variables latentes pour expliquer le choix modal. Après une revue de littérature sur les modèles de choix hybrides, c’est-à-dire des modèles combinant modèle d’équations structurelles et modèle de choix discret, un tel modèl
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Ashiabor, Senanu Y. "Modeling Intercity Mode Choice and Airport Choice in the United States." Diss., Virginia Tech, 2007. http://hdl.handle.net/10919/26221.

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The aim of this study was to develop a framework to model travel choice behavior in order to estimate intercity travel demand at nation-level in the United States. Nested and mixed logit models were developed to study national-level intercity transportation in the United States. A separate General Aviation airport choice model to estimates General Aviation person-trips and number of aircraft operations though more than 3000 airports was also developed. The combination of the General Aviation model and the logit models gives the capability to estimate a full spectrum of intercity travel dema
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Books on the topic "Travel Mode Choice"

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Dasgupta, M. Mode choice in travel to work in British cities, 1971-1981. Department of Geography, London School of Economics, 1989.

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Swait, Joffre Dan. Travel mode substitution in São Paulo: Estimates and implications for air pollution control. World Bank, Policy Research Dept., Public Economics Division, 1995.

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Frank, Lawrence D. An analysis of relationships between urban form (density, mix, and jobs: housing balance) and travel behavior (mode choice, trip generation, trip length, and travel time). Washington State Dept. of Transportation, 1994.

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Baber, Charles M. Validation of Baltimore regional travel demand model. Baltimore Regional Council of Governments Transportation Planning Division, 1992.

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Kollo, Hanna P. H. Regional travel forecasting model system for the San Francisco Bay Area. Metropolitan Transportation Commission, 1988.

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Chui, Margaret K. The value of travel time: New estimates developed using a speed-choice model. Texas Transportation Institute, Texas A&M University System, 1986.

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Kitamura, Ryuichi. MIDAS: A travel demand forecasting tool based on a dynamic model system of household demographics and mobility : final report. Ministerie van Verkeer en Waterstaat, Projectbureau Integrale Verkeers-en Vervoerstudies, 1992.

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Kennedy, Aileen. Internationalisation of services: An analysis of the factors influencing entry mode choice. University College Dublin, 1994.

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Single or joint venturing?: A comprehensive approach to foreign entry mode choice. Avebury, 1996.

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Langlois, Jacques. L'orientation, mode d'emploi. ERPI, 2010.

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Book chapters on the topic "Travel Mode Choice"

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Chen, Huey-Kuo. "Dynamic User-Optimal Mode Choice Models." In Dynamic Travel Choice Models. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-59980-4_8.

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Zhang, Junyi, and Harry Timmermans. "A Scobit-Based Travel Mode Choice Model." In Proceedings of the 2010 Academy of Marketing Science (AMS) Annual Conference. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11797-3_88.

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Poltimäe, Helen, and Mari Jüssi. "Factors Affecting Choice of Travel Mode in Tallinn." In Environmental Challenges in the Baltic Region. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56007-6_6.

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Langer, Dorothea, and Angelika C. Bullinger. "User Requirement? Travel Mode Choice Routines Across Different Trip Types." In HCI International 2020 – Late Breaking Papers: Digital Human Modeling and Ergonomics, Mobility and Intelligent Environments. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59987-4_9.

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Rahman, Farzana, Md Nasif Rabbi, and Md Ariful Islam. "Choice of Travel Mode for Work Trips for Dhaka City to Enhance Travel Experience." In Resilient and Responsible Smart Cities. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63567-1_5.

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Mallig, Nicolai, and Peter Vortisch. "Incorporating Stability of Mode Choice into an Agent-Based Travel Demand Model." In Communications in Computer and Information Science. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60285-1_3.

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Zhao, Pengxiang, Dominik Bucher, Henry Martin, and Martin Raubal. "A Clustering-Based Framework for Understanding Individuals’ Travel Mode Choice Behavior." In Lecture Notes in Geoinformation and Cartography. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-14745-7_5.

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Mandel, Benedikt, Marc Gaudry, and Werner Rothengatter. "A Disaggregate Box-Cox Logit Mode Choice Model of Intercity Passenger Travel in Germany." In The Econometrics of Major Transport Infrastructures. Palgrave Macmillan UK, 1997. http://dx.doi.org/10.1007/978-1-349-13977-4_2.

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Bolduc, Denis, Richard Laferrière, and Gino Santarossa. "Spatial Autoregressive Error Components in Travel Flow Models: An Application to Aggregate Mode Choice." In New Directions in Spatial Econometrics. Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-642-79877-1_4.

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Mohd Ali, Nur Fahriza, Ahmad Farhan Mohd Sadullah, Anwar P. P. Abdul Majeed, Mohd Azraai Mohd Razman, Chun Sern Choong, and Rabiu Muazu Musa. "Forecasting Daily Travel Mode Choice of Kuantan Travellers by Means of Machine Learning Models." In Lecture Notes in Electrical Engineering. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4597-3_89.

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Conference papers on the topic "Travel Mode Choice"

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Yang, Chen, Wei Wang, Zhibin Li, and Jian Lu. "Travel Mode Choice Based on Latent Variable Enriched Discrete Choice Model." In Second International Conference on Transportation Engineering. American Society of Civil Engineers, 2009. http://dx.doi.org/10.1061/41039(345)720.

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Jin, Xiangyu, Chao Wang, and Wenli Hu. "TRAVEL MODE CHOICE OF LONG-DISTANCE PASSENGERS." In International Symposium on Multidisciplinary Inclusive Education, Management and Legal Services (ISMIEMLS). Volkson Press, 2018. http://dx.doi.org/10.26480/ismiemls.01.2018.04.06.

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Yin, Huanhuan, Juan Li, and Hongzheng Zhao. "Public Transportation Travel Mode Choice Behavior Research." In The Twelfth COTA International Conference of Transportation Professionals. American Society of Civil Engineers, 2012. http://dx.doi.org/10.1061/9780784412442.136.

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Dexin Zhang and Lijing Song. "Travel mode choice behavior of taxi passengers." In 5th Advanced Forum on Transportation of China (AFTC 2009). IET, 2009. http://dx.doi.org/10.1049/cp.2009.1608.

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Xian-Yu, Jian-Chuan. "Travel Mode Choice Analysis Using Support Vector Machines." In 11th International Conference of Chinese Transportation Professionals (ICCTP). American Society of Civil Engineers, 2011. http://dx.doi.org/10.1061/41186(421)37.

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Yin, Huanhuan, Hongzhi Guan, Tong Liu, Liyuan Gong, and Juan Li. "Study of Urban Resident Travel Mode Choice Behavior." In Tenth International Conference of Chinese Transportation Professionals (ICCTP). American Society of Civil Engineers, 2010. http://dx.doi.org/10.1061/41127(382)195.

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Mi, Jun, Chuanqi Zhang, and Yang Zhang. "Urban Traveler Travel Mode Choice Equilibrium Model under the Condition of Bus Lanes." In Fifth International Conference on Transportation Engineering. American Society of Civil Engineers, 2015. http://dx.doi.org/10.1061/9780784479384.183.

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Jiao, Pengpeng, Meiqi Liu, and Xin Li. "Study on Travel Mode Choice Behavior Using Latent Class Model." In 10th Asia Pacific Transportation Development Conference. American Society of Civil Engineers, 2014. http://dx.doi.org/10.1061/9780784413364.007.

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Song, Mingzhu, Yi Zhang, Zuojun Max Shen, Meng Li, and Zhenning Dong. "Mode Shift from Car to Bike Shared: A Travel-Mode Choice Model." In 19th COTA International Conference of Transportation Professionals. American Society of Civil Engineers, 2019. http://dx.doi.org/10.1061/9780784482292.209.

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Zhou, Xuemei, Xiaoguang Yang, and Yunteng Lao. "Public Transport Service Level Influence on Travel Mode Choice." In First International Conference on Transportation Engineering. American Society of Civil Engineers, 2007. http://dx.doi.org/10.1061/40932(246)668.

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Reports on the topic "Travel Mode Choice"

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Singleton, Patrick. Exploring the Positive Utility of Travel and Mode Choice. Portland State University Library, 2000. http://dx.doi.org/10.15760/etd.5664.

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Adkins, Arlie. Determinants of Recent Mover Non-work Travel Mode Choice. Portland State University Library, 2000. http://dx.doi.org/10.15760/etd.1918.

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Javanmardi, Mahmoud. Mode Choice Modeling Using Personalized Travel Time and Cost Data. University of South Florida, 2015. http://dx.doi.org/10.5038/cutr-nctr-rr-2015-07.

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Broach, Joseph. Travel Mode Choice Framework Incorporating Realistic Bike and Walk Routes. Portland State University Library, 2000. http://dx.doi.org/10.15760/etd.2698.

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Wang, Chih-Hao, and Na Chen. Do Multi-Use-Path Accessibility and Clustering Effect Play a Role in Residents' Choice of Walking and Cycling? Mineta Transportation Institute, 2021. http://dx.doi.org/10.31979/mti.2021.2011.

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The transportation studies literature recognizes the relationship between accessibility and active travel. However, there is limited research on the specific impact of walking and cycling accessibility to multi-use paths on active travel behavior. Combined with the culture of automobile dependency in the US, this knowledge gap has been making it difficult for policy-makers to encourage walking and cycling mode choices, highlighting the need to promote a walking and cycling culture in cities. In this case, a clustering effect (“you bike, I bike”) can be used as leverage to initiate such a trend
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Abrego, Lisandro, and John Whalley. The Choice of Structural Model in Trade-Wages Decompositions. National Bureau of Economic Research, 1999. http://dx.doi.org/10.3386/w7312.

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Russ, Katheryn, and Diego Valderrama. Financial Choice in a Non-Ricardian Model of Trade. National Bureau of Economic Research, 2009. http://dx.doi.org/10.3386/w15528.

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Sabogal-Cardona, Orlando, Lynn Scholl, Daniel Oviedo, Amado Crotte, and Felipe Bedoya. Not My Usual Trip: Ride-hailing Characterization in Mexico City. Inter-American Development Bank, 2021. http://dx.doi.org/10.18235/0003516.

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With a few exceptions, research on ride-hailing has focused on North American cities. Previous studies have identified the characteristics and preferences of ride-hailing adopters in a handful of cities. However, given their marked geographical focus, the relevance and applicability of such work to the practice of transport planning and regulation in cities in the Global South is minimal. In developing cities, the entrance of new transport services follows very different trajectories to those in North America and Europe, facing additional social, economic, and cultural challenges, and involvin
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Yang, Liu-Qin, Brad Wipfli, Lee Cyr, Kristina Currans, and Liming Wang. How Do Stressed Workers Make Travel Mode Choices That Are Good For Their Health, Safety, and Productivity? National Institute for Transportation and Communities (NITC), 2018. http://dx.doi.org/10.15760/trec.190.

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Bedoya-Maya, Felipe, Lynn Scholl, Orlando Sabogal-Cardona, and Daniel Oviedo. Who uses Transport Network Companies?: Characterization of Demand and its Relationship with Public Transit in Medellín. Inter-American Development Bank, 2021. http://dx.doi.org/10.18235/0003621.

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Transport Network Companies (TNCs) have become a popular alternative for mobility due to their ability to provide on-demand flexible mobility services. By offering smartphone-based, ride-hailing services capable of satisfying specific travel needs, these modes have transformed urban mobility worldwide. However, to-date, few studies have examined the impacts in the Latin American context. This analysis is a critical first step in developing policies to promote efficient and sustainable transport systems in the Latin-American region. This research examines the factors affecting the adoption of o
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