Integrated Choice and Latent Variable Models for evaluating Flexible Transport Mode choice

Politis, Ioannis; Papaioannou, Panagiotis; Basbas, Socrates

doi:10.1016/j.rtbm.2012.06.007

Cited by 20 publications

(7 citation statements)

References 17 publications

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“…Mitra et al [23] and Lee et al [24] analyzed the relationship between potential safety measures and severity of road accidents in transport planning. Gopinath [25], Morikawa et al [21], Walker and Ben-Akiva [26], Johansson et al [27], Yáñez et al [28], and Politis et al [29] added the influence of traveler's aptitude and perception into their models and integrated it into demand forecasting models. Shiftan et al [30] explored the causal relationship between latent variables (time sensibility, determined travel plan, aspiration to use transport vehicle, etc.)…”

Section: Introductionmentioning

confidence: 99%

Mode Choice Model for Public Transport with Categorized Latent Variables

Chen

2017

Mathematical Problems in Engineering

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Mode choice model for public transport, which integrates structural equation model (SEM) and discrete choice model (DCM) with categorized latent variables, was presented in this paper. Apart from identifying those important latent variables that affect mode choice for public transport, the objective of this study was also to develop an improved disaggregative model that better explains travel behavior of those decision-makers in choosing public transport. After extensive observations, selective latent variable sets which consist of latent variable components were chosen together with explicit variables in formulating the utility functions. Data collected in Chengdu city, China, were used to calibrate and validate the model. Results showed that the impact of fare on mode choice of public transport escalated in the SEM-DCM integrated model compared with the traditional logit model. The goodness of fit for the integrated model with latent variable sets is 0.201 higher than that of the traditional logit model, which proves that latent variables have an obvious impact on mode choice behavior, and the SEM-DCM integrated model has higher accuracy and stronger explanatory ability. The results are especially helpful for public transport operators to achieve higher mode share split by improving the service quality of public transport in terms of providing more convenience and better service environment for public transport users.

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Section: Introductionmentioning

confidence: 99%

Mode Choice Model for Public Transport with Categorized Latent Variables

Chen

2017

Mathematical Problems in Engineering

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“…Descriptive statistical analysis is a statistical method that uses mathematical language to describe sample characteristics or explain the relationship between variables [ 43 ]. A total of 184 valid samples were statistically analyzed, and the results are shown in Table 5 .…”

Section: Resultsmentioning

confidence: 99%

“…In recent years, scholars have used various methods to construct evaluation indicators for different research objects. Commonly used methods include literature review [ 42 ], questionnaire survey [ 43 ], case analysis [ 44 ], semi-structured interview [ 45 ], the Delphi method [ 46 ], multi-criteria decision-making [ 47 ], and grounded theory [ 48 ]. Based on the complexity of the projects, the methods used in this study include literature analysis, policy texts, expert interviews, grounded theory, questionnaire survey, and factor analysis to comprehensively and systematically sort out, summarize, and filter the O&M management indicators of mega infrastructure projects so as to build a complete, effective, and comprehensive indicator system.…”

Section: Literature Reviewmentioning

confidence: 99%

An Indicator System for Evaluating Operation and Maintenance Management of Mega Infrastructure Projects in China

Chen

Pan

Jia

et al. 2020

IJERPH

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Mega infrastructure projects provide a basic guarantee for social development, economic construction, and livelihood improvement. Their operation and maintenance (O&M) management are of great significance for the smooth operation and the realization of the value created by the projects. In order to provide an approach for effectively evaluating O&M management, this study develops a holistic indicator system using a mixed-review method from the national macro perspective in China. In this study, literature analysis, policy texts, expert interviews, and grounded theory were used to collect relevant data at home and abroad, and establish an initial evaluation indicator system with 23 indicators covering two dimensions and five aspects. Then the questionnaire survey and factor analysis were used to score and categorize the indicators, and finally an evaluation indicator system for O&M management of mega infrastructure projects was formed. The results show that social relations, environmental benefits, macro policy, and operational capacities play an important role in the evaluation of the O&M of mega infrastructure projects. This study helps the management team to avoid negative impacts in the O&M management of mega infrastructure projects and lays a theoretical foundation for future research. The indicator system in this study is based on the Chinese context, and it remains to be verified whether the indicator system is applicable to other countries due to the differences in political and cultural backgrounds in different regions.

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“…Reducing actual and perceived travel time by bus and bicycle would greatly impact commuting patterns [ 29 , 30 ]. Politis [ 31 ] pointed out the factors contributing to the acceptance of sustainable mobility measures for university commuters by means of factor analysis and SEM, highlighting the priority role played by individual travel choices (car dependency). The work of Papaioannou and Politis [ 32 ] examined the impact produced by endogenous characteristics of commuters belonging to a large university community on their travel mode choices, combining the behavioural change model with the discrete choice modelling approach.…”

Section: Introductionmentioning

confidence: 99%

A Cluster Analysis of University Commuters: Attitudes, Personal Norms and Constraints, and Travel Satisfaction

Angelis

Mantecchini

Pietrantoni

2021

IJERPH

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Higher education institutions are recognised as settings where the community’s awareness of sustainable mobility can be strengthened or reshaped. The first objective of the present study was to identify groups of commuters based on their modal choice in a large higher education institution in Italy. The second objective was to compare the groups on socio-demographic and psychosocial variables, specifically attitudes, personal norms, personal constraints, and travel satisfaction. The cluster analysis revealed five different types of commuters: car-oriented, two-wheeled urban users, pedestrians, long-distance commuters, and regular bus users. Attitudes, personal constraints and norms, and satisfaction differed in the five groups of commuters. The present study provides insights for behavioural change programmes and organizational policies on sustainable mobility.

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Integrated Choice and Latent Variable Models for evaluating Flexible Transport Mode choice

Cited by 20 publications

References 17 publications

Mode Choice Model for Public Transport with Categorized Latent Variables

Mode Choice Model for Public Transport with Categorized Latent Variables

An Indicator System for Evaluating Operation and Maintenance Management of Mega Infrastructure Projects in China

A Cluster Analysis of University Commuters: Attitudes, Personal Norms and Constraints, and Travel Satisfaction

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