Latent lifestyle and mode choice decisions when travelling short distances

Prato, Carlo Giacomo; Halldórsdóttir, Katrín; Nielsen, Otto Anker

doi:10.1007/s11116-016-9703-9

Cited by 37 publications

(6 citation statements)

References 50 publications

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“…The findings from cross-sectional analysis show that the correlation between neighbourhood characteristics and car ownership is primarily the result of self-selection. Apart from the SEM approach, some recent studies have adopted other modelling techniques such as latent class and random effect modelling through discrete choice analysis (Walker and Li 2007;Liao et al 2015;Prato 2015) or propensity scoring and direct matching (McDonald and Trowbridge 2009) to control for endogeneities. Notably, Liao et al (2015) examine the residential preferences for compact development in the State of Utah whilst controlling for heterogeneity in residential location choice arising from household socio-economic backgrounds and attitudes.…”

Section: Literature Reviewmentioning

confidence: 99%

The built environment typologies in the UK and their influences on travel behaviour: new evidence through latent categorisation in structural equation modelling

Jahanshahi

Jin

2015

Transportation Planning and Technology

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This paper uses a new latent categorisation approach (LCA) in structural equation modelling (SEM) to gain fresh insights into the influence of the built environment characteristics upon travel behaviour. So far as we are aware, this is the first LCA-SEM application in this field. We use all the main descriptors of the built environment in the UK National Travel Survey data in the analysis whilst accounting for the high correlations among the descriptorsthis is achieved through defining a categorical rather than continuous latent variable for the built environment characteristics. This novel approach to defining a tangible typology of the built environment in the UK is capable of making the analytical results more cogent to formulating new, proactive land use planning and urban design measures as well as monitoring the outcomes of ongoing planning and transport interventions. Since travel survey data are regularly collected across a large number of cities in the world, our approach helps to guide the design of future travel surveys for those cities in a way that enhances the analysis and monitoring of the impacts of planning and transport policies on travel choices.

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Section: Literature Reviewmentioning

confidence: 99%

The built environment typologies in the UK and their influences on travel behaviour: new evidence through latent categorisation in structural equation modelling

Jahanshahi

Jin

2015

Transportation Planning and Technology

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“…The LC model identifies a finite number of latent classes with heterogeneous characteristics and adopts the specific choice model to estimate individuals' preferences using homogenous features [39,40]. At present, the LC model has been widely used in many related choice studies, such as the mode decision process [41,42], vehicle ownership [43], residential location [44], willingness-to-pay for vehicles [45], and so on. It was proven that the LC model outperforms the traditional logit models in terms of the goodness of fit [46].…”

Section: Discrete Models Of Travel Behaviormentioning

confidence: 99%

Analyzing Commute Mode Choice Using the LCNL Model in the Post-COVID-19 Era: Evidence from China

Luan

Yang

Jiang

et al. 2022

IJERPH

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The purpose of this paper is to gain an insight into commuting and travel mode choices in the post-COVID-19 era. The surveys are divided into two waves in Qingdao, China: the first-wave questionnaires were collected under the background of a three-month zero growth of cases; the second wave was implemented after the new confirmed cases of COVID-19. The latent class nested logit (LCNL) model is applied to capture heterogeneous characteristics among the various classes. The results indicate that age, income, household composition, and the frequency of use of travel modes are latent factors that impact users’ attitudes toward mass transit and the private car nests when undergoing the shock of the COVID-19 pandemic. Individuals’ trepidation regarding health risks began to fade, but this is still a vital consideration in terms of mode choice and the purchase of vehicles. Moreover, economic reinvigoration, the increase in car ownership, and an increase in the desire to purchase a car may result in great challenges for urban traffic networks.

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“…e seed OD matrix is derived from the calculation of interval-valued impedance. By using the command of "Networks/Paths-Multiple Paths" in TransCAD software, the travel distances or travel times of several shortest paths between the centroid points of different traffic zones in the road network of Academy Street historic district can be calculated, which can be used as the travel impedance matrix between traffic zones, and then, the seed OD matrix can be calculated according to Equation (22), and the current OD matrix of each traffic zone is obtained by using the OD backstepping method, as shown in Table 1:…”

Section: Travel Mode Optimal Sharing Forecastmentioning

confidence: 99%

“…Advances in Civil Engineering private transportation. For example, Prato et al [22] compared public transport and private transport in Copenhagen Region when traveling short distance and established a differential equation model of traffic competition under the restriction of urban transport ecological carrying capacity. Tabuchi [23] studied the competition between the two modes of transportation under different charging systems.…”

Section: Introductionmentioning

confidence: 99%

Traffic Structure Optimization in Historic Districts Based on Green Transportation and Sustainable Development Concept

Wang

Sun

2019

Advances in Civil Engineering

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To perform the reasonable traffic structure in the historical districts and effectively alleviate the contradiction between limited traffic supply and rapid growth of the traffic demand in historical districts, a dynamic game model of traffic competition is established in this paper, aiming at the green transportation and sustainable development. Firstly, the logit model reflecting the sharing rate of the traffic mode is established by using the generalized cost method to quantify all the factors that influence the travel mode selection. Accordingly, a dynamic game model of complete information is established for the trip mode of historical districts, taking into account the economic sustainability, environmental sustainability, and social sustainability of the traffic development. The model is based on the goal of maximizing the generalized profit, and modeling with environmental pollution, energy utilization, and road service level as the common constraints of various traffic modes. By iterating the Nash equilibrium solution of the model, the optimal structure and the optimal share of the traffic modes in the historical districts can be predicted. Finally, the model presented in the study is verified by the historical districts of Academy Street in Zhengzhou city, China, and the optimal structure and optimal traffic share of each traffic mode in the block are obtained. By changing the constraint conditions of the model, two sets of different governance policies are compared and analyzed, and some feasible suggestions on improvement of traffic structure are also put forward. The research results can be the important reference for traffic planning in historic districts.

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Latent lifestyle and mode choice decisions when travelling short distances

Cited by 37 publications

References 50 publications

The built environment typologies in the UK and their influences on travel behaviour: new evidence through latent categorisation in structural equation modelling

The built environment typologies in the UK and their influences on travel behaviour: new evidence through latent categorisation in structural equation modelling

Analyzing Commute Mode Choice Using the LCNL Model in the Post-COVID-19 Era: Evidence from China

Traffic Structure Optimization in Historic Districts Based on Green Transportation and Sustainable Development Concept

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