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Journal articles on the topic 'Choice of mode'

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Published: 3 June 2025

Last updated: 31 July 2025

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1

Subhro Mitra. "Discrete Choice Model of Agricultural Shipper's Mode Choice." Transportation Journal 52, no. 1 (2013): 6. http://dx.doi.org/10.5325/transportationj.52.1.0006.

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Sanches, Suely da Penha, and Fabiana Serra de Arruda. "Incorporating Nonmotorized Modes in a Mode Choice Model." Transportation Research Record: Journal of the Transportation Research Board 1818, no. 1 (2002): 89–93. http://dx.doi.org/10.3141/1818-14.

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3

Yang, S., Wei Deng, D. X. Wu, and W. Gong. "Analysis of the Interrelationship between Trip Chain Pattern and Trip Mode Choice Based on Multinomial Logistic Model." Applied Mechanics and Materials 743 (March 2015): 407–12. http://dx.doi.org/10.4028/www.scientific.net/amm.743.407.

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This paper explores the interrelationship between trip chain pattern and trip mode choice based on multinomial logistic model, using 2010 Nanjing resident trip survey data. Unlike previous literatures, trip mode choice is divided into single-mode and multi-modes in this study. Estimation coefficients verify trip chain pattern and trip mode selection are a pair of choices that influence each other. Trip mode is great positively associated with trip chain pattern of HW+WH, HO+OH, HW+OH, however, in return trip chain pattern is the most significant negative factor that affects trip mode choice, w

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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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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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Hwang, Jung-Hoon. "A Comparative Analysis of Characteristics of Mode Choice and Mode Transfer to Public Transit by Mode-Choice Class for the Effective Transportation Demand Management Implement." Journal of the Korean Society of Civil Engineers 33, no. 6 (2013): 2493. http://dx.doi.org/10.12652/ksce.2013.33.6.2493.

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Timmermans, H. J. P. "A Stated Choice Model of Sequential Mode and Destination Choice Behaviour for Shopping Trips." Environment and Planning A: Economy and Space 28, no. 1 (1996): 173–84. http://dx.doi.org/10.1068/a280173.

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Stated preference and choice models currently used in urban planning are focused on predicting single choices. In this paper the intention is to extend these modelling approaches to the case of sequential choice behaviour. Design strategies and model specifications that allow one to predict sequential choice are discussed. The approach is illustrated in a study of sequential mode and destination choice behaviour for shopping trips. The research findings suggest that the proposed approach may be a valuable extension of currently available stated preference and choice methods to analyse more com

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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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9

Xu, Gangxiang, Bin Guo, Wen Li, and Xiaoting Wang. "Foreign sequential entry mode choice." Baltic Journal of Management 13, no. 4 (2018): 544–63. http://dx.doi.org/10.1108/bjm-09-2017-0280.

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Purpose The purpose of this paper is to use the theoretical perspective of structural inertia as a unique lens to study foreign sequential entry mode choices of multinational firms. Design/methodology/approach It adopts quantitative analysis of a sample of 121 Chinese publicly listed firms with 564 foreign entry incidents in the 2001-2012 period to test the hypotheses. Findings The empirical results show that multinational firms have a tendency to adopt the same mode in the subsequent entry as the number of prior entry mode choice of a given type (joint venture (JV) in this study) increases. T

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Moslem, Sarbast, Tiziana Campisi, Agnieszka Szmelter-Jarosz, Szabolcs Duleba, Kh Md Nahiduzzaman, and Giovanni Tesoriere. "Best–Worst Method for Modelling Mobility Choice after COVID-19: Evidence from Italy." Sustainability 12, no. 17 (2020): 6824. http://dx.doi.org/10.3390/su12176824.

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All countries have suffered from the COVID-19 crisis; the pandemic has adversely impacted all sectors. In this study, we examine the transport sector with a specific focus on the problem of commuting mode choice and propose a new decision-making approach for the alternative modes after synthesizing expert opinions. As a methodology, a customized model of the recently developed best–worst method (BWM) is used to evaluate mobility choice alternatives. The survey reflects citizens’ opinions toward mobility choices in two Italian cities, Palermo and Catania, before and during the pandemic. BWM is

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Lu, Huan, and Hongcheng Gan. "Unraveling the Influence of Perceived Built Environment on Commute Mode Choice Based on Hybrid Choice Model." Applied Sciences 14, no. 17 (2024): 7921. http://dx.doi.org/10.3390/app14177921.

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To address the limitations of existing studies on the built environment and commute mode choice, which primarily focus on the objective and residential built environment, this study investigates how commuters’ perceptions of the built environment at their residences and workplaces influence their choice of commuting mode. First, six latent variables are proposed to characterize the perceived built environment. Then, commuters’ socio-economic and commuting characteristics are treated as exogenous variables. Subsequently, the influence of the perceived built environment on commute mode choice is

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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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KATO, Hironori, Yoshimasa NAKAJIMA, and Makoto IMAI. "Payment Mode Choice Model including Route Choice in Urban Railway Service." INFRASTRUCTURE PLANNING REVIEW 19 (2002): 447–52. http://dx.doi.org/10.2208/journalip.19.447.

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Shakeel, Kiran, Taha Hossein Rashidi, and Travis S. Waller. "Choice Set Formation Behavior: Joint Mode and Route Choice Selection Model." Transportation Research Record: Journal of the Transportation Research Board 2563, no. 1 (2016): 96–104. http://dx.doi.org/10.3141/2563-14.

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TOMINAGA, Masahiro, Hiroshi SHIMAMOTO, Nobuhiro UNO, Jan-Dirk SCHMÖCKER, Toshiyuki NAKAMURA, and Hiroki YAMAZAKI. "COMBINED MODE AND ROUTE CHOICE EQUILIBRIUM MODEL CONSIDERING HETEROGENEITY IN TRANSPORTATION CHOICES." Journal of Japan Society of Civil Engineers, Ser. D3 (Infrastructure Planning and Management) 71, no. 5 (2015): I_443—I_450. http://dx.doi.org/10.2208/jscejipm.71.i_443.

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Yoshida, Akira, and Noboru Harata. "A Mixed Mode Choice Model Including Railway Route, Stations, and Its Access and Egress Mode Choice." Doboku Gakkai Ronbunshu, no. 542 (1996): 19–31. http://dx.doi.org/10.2208/jscej.1996.542_19.

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Franklin, Joel P., and Debbie A. Niemeier. "Discrete Choice Elasticities for Elderly and Disabled Travelers Between Fixed-Route Transit and Paratransit." Transportation Research Record: Journal of the Transportation Research Board 1623, no. 1 (1998): 31–36. http://dx.doi.org/10.3141/1623-05.

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In the current practice of mode-choice modeling, models typically focus on the more traditional choices, such as those between automobile, transit, and nonmotorized transportation. For most travelers these are, indeed, the most relevant modes. However, for some segments of the population, particularly the elderly, the choice is more limited. This study investigates the factors that affect the elderly and disabled travelers’ choice between public transit and paratransit. Data collected from the public transit service, Sacramento Regional Transit, and the paratransit service, Paratransit, Inc.,

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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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19

Kariyana, I. M., T. H. Pamungkas, T. A. Anggraini, and G. Sumarda. "Urban Transportation Mode Choice Model in Bali." Civil Engineering and Architecture 12, no. 6 (2024): 4031–44. http://dx.doi.org/10.13189/cea.2024.120619.

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Rich, J., P. M. Holmblad, and C. O. Hansen. "A weighted logit freight mode-choice model." Transportation Research Part E: Logistics and Transportation Review 45, no. 6 (2009): 1006–19. http://dx.doi.org/10.1016/j.tre.2009.02.001.

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Norojono, O., and W. Young. "A Stated preference freight mode choice model." Transportation Planning and Technology 26, no. 2 (2003): 1. http://dx.doi.org/10.1080/715020600.

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22

Sivasubramaniyam, Rathee D., Samuel G. Charlton, and Rebecca J. Sargisson. "Mode choice and mode commitment in commuters." Travel Behaviour and Society 19 (April 2020): 20–32. http://dx.doi.org/10.1016/j.tbs.2019.10.007.

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Novi Wulansari, Dwi, and Milla Dwi Astari. "Mode choice analysis using discrete choice model from transport user (Case study: Jakarta LRT, Indonesia)." MATEC Web of Conferences 181 (2018): 03001. http://dx.doi.org/10.1051/matecconf/201818103001.

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Jakarta Light Rail Transit (Jakarta LRT) has been planned to be built as one of mass rail-based public transportation system in DKI Jakarta. The objective of this paper is to obtain a mode choice models that can explain the probability of choosing Jakarta LRT, and to estimate the sensitivity of mode choice if the attribute changes. Analysis of the research conducted by using discrete choice models approach to the behavior of individuals. Choice modes were observed between 1) Jakarta LRT and TransJakarta Bus, 2) Jakarta LRT and KRL-Commuter Jabodetabek. Mode choice model used is the Binomial Lo

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Hasnine, Md Sami, and Khandker Nurul Habib. "What about the dynamics in daily travel mode choices? A dynamic discrete choice approach for tour-based mode choice modelling." Transport Policy 71 (November 2018): 70–80. http://dx.doi.org/10.1016/j.tranpol.2018.07.011.

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Wu, Jingxian, Min Yang, Shangjue Sun, and Jingyao Zhao. "Modeling Travel Mode Choices in Connection to Metro Stations by Mixed Logit Models: A Case Study in Nanjing, China." PROMET - Traffic&Transportation 30, no. 5 (2018): 549–61. http://dx.doi.org/10.7307/ptt.v30i5.2623.

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Urban rail transit trips usually involve multiple stages, which can be differentiated in terms of transfers that may involve distinct access and egress modes. Most studies on access and egress mode choices of urban rail transit have separately examined the two mode choices. However, in reality, the two choices are temporally correlated. This study, therefore, has sequentially applied the mixed logit to examine the contributors of access and egress mode choices of urban metro commuters using the data from a recent survey conducted in Nanjing, China. 9 typical multimodal combinations constituted

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Mitra, Subhro, and Steven M. Leon. "Discrete choice model for air-cargo mode selection." International Journal of Logistics Management 25, no. 3 (2014): 656–72. http://dx.doi.org/10.1108/ijlm-04-2012-0027.

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Purpose – The purpose of this paper is to develop a better understanding of the factors that influence a shipper's decision to choose air cargo as a mode of shipment. Design/methodology/approach – A disaggregate multinomial discrete choice model is developed using freight shipment survey data to identify critical factors influencing air cargo mode choice. Disaggregate revealed preference data is obtained from surveying 347 manufacturers, freight forwarders, and other third-party service providers. Findings – The empirical model developed in this research shows that the rate of shipment, time o

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Zhang, Jian, Chun Jing Ma, Xiang Feng Ji, and Gang Zhong. "Modeling and Sensitivity Analysis for Railway Passengers’ Public Transit Mode Choice." Applied Mechanics and Materials 641-642 (September 2014): 678–84. http://dx.doi.org/10.4028/www.scientific.net/amm.641-642.678.

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Comprehensive terminal integrates different modes of transport and sharing rates of different traffic modes influence its planning greatly. To determine the sharing rates, it’s necessary to study mode choice probability of passengers. Based on the theory of disaggregate choice, with the survey of mode choices of passengers arriving by rail in Nanjing south railway station, this paper establishes multinomial logit (MNL) model and nest logit (NL) model, considering three types of modes of transport including the subway, regular bus, and taxi. Models are calibrated with SPSS and validated through

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Outwater, Maren L., Steve Castleberry, Yoram Shiftan, Moshe Ben-Akiva, Yu Shuang Zhou, and Arun Kuppam. "Attitudinal Market Segmentation Approach to Mode Choice and Ridership Forecasting: Structural Equation Modeling." Transportation Research Record: Journal of the Transportation Research Board 1854, no. 1 (2003): 32–42. http://dx.doi.org/10.3141/1854-04.

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The San Francisco Bay Area Water Transit Authority is evaluating expanded ferry service, as required by the California Legislature. As part of this process, Cambridge Systematics developed forecasts using a combination of market research strategies and the addition of nontraditional variables into the mode choice modeling process. The focus of this work was on expanding the mode choice model to recognize travelers' attitudes and different market segments. Structural equation modeling was used to simultaneously identify the attitudes of travel behaviors and the causal relationships between trav

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Hermawan, Antony, Andri Irfan Rifai, and Susanty Handayani. "Analysis of Student Mode Selection Behavior at Batam International University." Indonesian Journal of Multidisciplinary Science 1, no. 1 (2022): 1–16. http://dx.doi.org/10.55324/ijoms.v1i1.318.

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University students in many developing countries do not experience the same mode choices in developed countries. This study implements existing influence factors of mode choice towards a university in a developing country by analyzing the characteristics of the student’s preferences in choosing the best transportation modes under different circumstances. The primary data is taken through a stated preference survey which is then analyzed using a descriptive statistics approach and findings are compared with existing studies. Firstly, commuter students show a significant interest in driving-alon

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Fan, Aihua, Xumei Chen, and Tao Wan. "How Have Travelers Changed Mode Choices for First/Last Mile Trips after the Introduction of Bicycle-Sharing Systems: An Empirical Study in Beijing, China." Journal of Advanced Transportation 2019 (May 14, 2019): 1–16. http://dx.doi.org/10.1155/2019/5426080.

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In recent years, there has been rapid development in bicycle-sharing systems (BSS) in China. Moreover, such schemes are considered promising solutions to the first/last mile problem. This study investigates the mode choice behaviors of travelers for first/last mile trips before and after the introduction of bicycle-sharing systems. Travel choice models for first/last mile trips are determined using a multinomial logit model. It also analyzes the differences in choice behavior between the young and other age groups. The findings show that shared bicycles become the preferred mode, while travele

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Wei, Chong, Lin Xiao, and Chun Fu Shao. "Mode Choice Behavior Analysis by Using a Semi-Compensatory Discrete Choice Model." Advanced Materials Research 838-841 (November 2013): 3300–3304. http://dx.doi.org/10.4028/www.scientific.net/amr.838-841.3300.

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In this study we proposed a semi-compensatory model to analyze the mode choice behavior. The proposed model formulated the conjunctive rule through a straightforward way. The proposed model can take into account the probability distribution of the threshold involved by the conjunctive rule. To estimate the parameters of the proposed model, we derived the posterior distribution of the parameters by using the Bayes theorem and developed a blacked Metropolis-Hastings algorithm to carry out the estimation based on the posterior distribution. We also employed the data augmentation technology to sim

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García-Melero, Gustavo, Rubén Sainz-González, Pablo Coto-Millán, and Alejandra Valencia-Vásquez. "Ridesourcing mode choice: A latent class choice model for UberX in Chile." Transportation Research Interdisciplinary Perspectives 16 (December 2022): 100722. http://dx.doi.org/10.1016/j.trip.2022.100722.

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Nurul Habib, Khandker. "A Heteroscedastic Polarized Logit Model to Investigate the Competition of Bicycle for the Bikeable Trips with the Other Modes." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 49 (2018): 58–68. http://dx.doi.org/10.1177/0361198118796357.

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The paper proposes a new discrete choice model, named the Heteroscedastic Polarized Logit (HPL) to investigate choice contexts with one or more alternatives with remarkably low market shares. The proposed model is used to investigate the factors influencing the choice of a bicycle as a travel mode in the National Capital Region (NCR) of Canada. Data from the latest household travel survey of the NCR are used to investigate the mode choices of bikeable trips. Bikeable trips are defined as trips with lengths shorter than 16 km as this is the observed maximum limit of a bicycle trip in the datase

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Fariz, Umar, Nahry, and Gloriani Christin. "Transportation Mode Choice and Sustainability." Jurnal Kepariwisataan: Destinasi, Hospitalitas dan Perjalanan 8, no. 1 (2024): 35–44. http://dx.doi.org/10.34013/jk.v8i1.1338.

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This study conducted in Bandung Regency delves into the factors influencing the choice of transportation modes for tourists and provides practical insights. Specifically, the research examines the influence of park-and-ride security, travel time savings, and travel costs on the selection of private vehicles and shuttle buses. The findings emphasize the importance of sustainable transportation facilities and efficient public transport services, offering a practical roadmap for addressing transportation needs for tourists in Bandung Regency. With a focus on the park-and-ride concept, this resear

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Abdelwahab, W. M., and M. A. Sargious. "A simultaneous decision-making approach to model the demand for freight transportation." Canadian Journal of Civil Engineering 18, no. 3 (1991): 515–20. http://dx.doi.org/10.1139/l91-062.

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The application of discrete choice models (e.g., logit, probit) to study modal choice in passenger transportation has had a wide acceptance in the literature. However, little success had been reported on the application of these models to study the demand for freight transportation. This is mainly because in freight transportation a model that merely attempts to explain the choice of mode without taking into consideration other related factors, such as shipment size, is only one part of a complete model. Another type of models known as inventory-based models, which takes these factors into con

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Han, Yan, Hong Zhi Guan, and Meng Xue. "Preferred Mode Choice Model for Commuter Purpose Based on Multinominal Logit Model." Applied Mechanics and Materials 97-98 (September 2011): 570–75. http://dx.doi.org/10.4028/www.scientific.net/amm.97-98.570.

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As a quasi-public traffic mode, more and more attention has been paid to the commuter bus to ease the traffic congestion. To get the travel behaviors of the commuters to which the commuter bus is available, The RP and SP survey about the travel behavior of commuters were carried out and the influencing factors of mode choice are discussed. The commuting mode combinations were found to exist during the decision-making process and there exist the preferred mode and secondary mode for each individual for one trip mode choice. The preferred mode choice model is established based on the multinomial

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Andrian, Andrian, Renni Anggraini, and Sugiarto Sugiarto. "ANALISIS KARAKTERISTIK RESPONDEN DAN ATRIBUT PERJALANAN TERHADAP PEMILIHAN MODA ANGKUTAN UMUM RUTE BANDA ACEH – TAPAKTUAN." Jurnal Arsip Rekayasa Sipil dan Perencanaan 2, no. 4 (2019): 294–304. http://dx.doi.org/10.24815/jarsp.v2i4.14946.

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The variance of transport modes may affect decision of mode choices for user to travel between the cities. Differences of characteristic transport modes add some value for the user in mode choices. Banda Aceh as a capital city of Aceh became the vital point as the center activities of Aceh province. Distibution of commodites and services is linked between Banda Aceh and the other cities in Aceh province, an example with Tapaktuan which in the between south-west road of Aceh province as distibution of commodites and services from and towards Banda Aceh. The purposes of this study aim for the an

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Li, ShuGuang, and QingHua Zhou. "Dynamic Combined-Mode Traffic Network Model considering Transfer Behaviors." Journal of Advanced Transportation 2020 (September 21, 2020): 1–15. http://dx.doi.org/10.1155/2020/2010875.

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We propose a dynamic combined-mode traffic network model considering transfer behaviors. We assume that travelers can be classified into two classes: one class is pure-mode travelers who complete a trip by single transportation mode, and another is combined-mode travelers who cover a journey by car, bus, and so forth. The multimode point queue model is used to model the interaction of cars and buses on the network. We present an integrated variational inequality formulation to capture the complex traveler choice behaviors such as departure time choices, transfer point, and route choices. Final

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KAWAKAMI, Shogo, and Shoshi MIZOKAMI. "A simultaneous estimation for mode choice function and equilibrium flows using a binary mode choice/assignment combined model." Doboku Gakkai Ronbunshu, no. 371 (1986): 79–87. http://dx.doi.org/10.2208/jscej.1986.371_79.

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Jung, You-Jin, and Jeffrey M. Casello. "Magnitude of mode constants in transit mode choice." International Journal of Sustainable Transportation 14, no. 10 (2019): 777–87. http://dx.doi.org/10.1080/15568318.2019.1627620.

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Ali, Nur Fahriza Mohd, Ahmad Farhan Mohd Sadullah, Anwar PP Abdul Majeed, Mohd Azraai Mohd Razman, Muhammad Aizzat Zakaria, and Ahmad Fakhri Ab Nasir. "Travel Mode Choice Modeling: Predictive Efficacy between Machine Learning Models and Discrete Choice Model." Open Transportation Journal 15, no. 1 (2021): 241–55. http://dx.doi.org/10.2174/1874447802115010241.

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Background: A complex travel behaviour among users is intertwined with many factors. Traditionally, the exploration in travel mode choice modeling has been dominated by the Discrete Choice model, nonetheless, owing to the advancement in computational techniques, machine learning has gained traction in understanding travel behavior. Aim: This study aims at predicting users’ travel model choice by means of machine learning models against a conventional Discrete Choice Model, i.e., Binary Logistic Regression. Objective: To investigate the comparison between machine learning models, namely Neural

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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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Ding, Chuan, Yu Chen, Jinxiao Duan, Yingrong Lu, and Jianxun Cui. "Exploring the Influence of Attitudes to Walking and Cycling on Commute Mode Choice Using a Hybrid Choice Model." Journal of Advanced Transportation 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/8749040.

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Transport-related problems, such as automobile dependence, traffic congestion, and greenhouse emissions, lead to a great burden on the environment. In developing countries like China, in order to improve the air quality, promoting sustainable travel modes to reduce the automobile usage is gradually recognized as an emerging national concern. Though there are many studies related to the physically active modes (e.g., walking and cycling), the research on the influence of attitudes to active modes on travel behavior is limited, especially in China. To fill up this gap, this paper focuses on exam

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Dill, Jennifer, and Erin Wardell. "Factors Affecting Worksite Mode Choice." Transportation Research Record: Journal of the Transportation Research Board 1994, no. 1 (2007): 51–57. http://dx.doi.org/10.3141/1994-07.

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Stæhr, Andreas Candefors, and Thomas Rørbeck Nørreby. "The metapragmatics of mode choice." Pragmatics and Society 12, no. 5 (2021): 756–81. http://dx.doi.org/10.1075/ps.20050.can.

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Abstract In this article, we investigate the use of social media in contemporary family interaction from a linguistic ethnographic perspective. Inspired by Auer’s (1998) work on code-switching in conversation, we study how family members choose and sometimes alternate between digitally mediated and face-to-face modes of communication in various family settings. Based on ethnographic observations, the participants’ metapragmatic reflections, and their interactional orientations to mode choices, we show how such choices serve social and metapragmatic functions in the interaction between family m

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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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Ermagun, Alireza, Taha Hossein Rashidi, and Zahra Ansari Lari. "Mode Choice for School Trips." Transportation Research Record: Journal of the Transportation Research Board 2513, no. 1 (2015): 97–105. http://dx.doi.org/10.3141/2513-12.

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Cohen, Arnold J., and Nigel G. Harris. "Mode choice for VFR journeys." Journal of Transport Geography 6, no. 1 (1998): 43–51. http://dx.doi.org/10.1016/s0966-6923(97)00038-0.

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Kamruzzaman, Md, Douglas Baker, Simon Washington, and Gavin Turrell. "Residential dissonance and mode choice." Journal of Transport Geography 33 (December 2013): 12–28. http://dx.doi.org/10.1016/j.jtrangeo.2013.09.004.

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Kahn, David, André De Palma, and Jean Louis Deneubourg. "Noisy demand and mode choice." Transportation Research Part B: Methodological 19, no. 2 (1985): 143–53. http://dx.doi.org/10.1016/0191-2615(85)90020-7.

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