Open Access
Open access
E3S Web of Conferences, volume 434, pages 2022

Study on the analysis of travel behavior: A review

Publication typeJournal Article
Publication date2023-10-12
SJR0.182
CiteScore0.9
Impact factor
ISSN22671242, 25550403
Abstract

Travel behavior analysis involves the utilization and examination of travel demand through the application of theories and analytical techniques derived from diverse scientific disciplines. There are many methods used by researchers in analyzing travel behavior. Mode selection is the stage where the transportation planning process is responsible for determining the travel load or knowing the number of people and goods, then selecting the available transportation models that serve as the starting point of the destination. Travel factors have a strong influence on a person’s travel behavior, (trip maker behavior), including income, vehicle ownership, vehicle condition, settlement density of one’s socioeconomic conditions. This paper describes the disadvantages and advantages of travel behavior modeling analysis and factors that influence the choice of modes based on travel behavior, so that in the future researchers can use it as an illustration in determining the right analysis.

Sukhov A., Friman M., Olsson L.E.
2023-09-01 citations by CoLab: 54 Abstract  
This study demonstrates the value of integrating different analytical perspectives to identify significant factors and characterize their importance. Specifically, we combine three analytical methods – partial least squares structural equation modeling (PLS-SEM), necessary condition analysis (NCA), and fuzzy set qualitative comparative analysis (fsQCA) – to create an expanded analytical process that enables informed decision-making. PLS-SEM identifies significant correlations between the predictor and outcome variables, NCA identifies critical bottlenecks required for a specific outcome, and fsQCA identifies configurations of conditions sufficient for producing a specific outcome. By applying this expanded analytical process to subjectively reported data on service quality and perceived accessibility, collected from five Nordic cities, we gain new insights into attracting an aging population to public transport. This study contributes to a better understanding of the nuances in the data, which is valuable for both research and practice.
Krueger R., Bierlaire M., Bansal P.
2023-07-01 citations by CoLab: 4 Abstract  
Ride-sourcing services offered by companies like Uber and Didi have grown rapidly in the last decade. Understanding the demand for these services is essential for planning and managing modern transportation systems. Existing studies develop statistical models for ride-sourcing demand estimation at an aggregate level due to limited data availability. These models lack foundations in microeconomic theory, ignore competition of ride-sourcing with other travel modes, and cannot be seamlessly integrated into existing individual-level (disaggregate) activity-based models to evaluate system-level impacts of ride-sourcing services. In this paper, we present and apply an approach for estimating ride-sourcing demand at a disaggregate level using discrete choice models and multiple data sources. We first construct a sample of trip-based mode choices in Chicago, USA by enriching household travel survey with publicly available ride-sourcing and taxi trip records. We then formulate a multivariate extreme value-based discrete choice model with sampling and endogeneity corrections to account for the construction of the estimation sample from multiple data sources and endogeneity biases arising from supply-side constraints and surge pricing mechanisms in ride-sourcing systems. Our analysis of the constructed dataset reveals insights into the influence of various socio-economic, land use and built environment features on ride-sourcing demand. We also derive elasticities of ride-sourcing demand relative to travel cost and time. Finally, we illustrate how the developed model can be employed to quantify the welfare implications of ride-sourcing policies and regulations such as terminating certain types of services and introducing ride-sourcing taxes.
Curtale R., Larsson J., Nässén J.
Tourism Management Perspectives scimago Q1 wos Q1
2023-06-01 citations by CoLab: 6 Abstract  
Possible strategies to mitigate the climate impact of tourism transport include encouraging tourism to closer destinations and supporting more sustainable modes of transport, including trains. Today international trips by railways only have a small market share but night trains are considered an important part of a future green Europe. However, little is known about travelers' preferences for night trains for long-distance travel in Europe. The results of an integrated choice and latent variable model (ICLV) applied to stated preference (SP) data collected from 1691 residents of Sweden show that, depending on place of origin in Sweden, in response to a set of innovations, including reduced travel time emanating from ongoing infrastructure investments, and the introduction of new, more comfortable trains, the share of plane users willing to switch to night trains to Central Europe could reach 20–30% and to Southern Europe, 6–10%.
Kante M., Michel B.
2023-05-01 citations by CoLab: 6 Abstract  
Structural equation modelling (SEM) is a statistical technique used in the field of Information Systems amongst others. The technique has been paid attention thanks to its flexibility and predictive power. However, there is a paucity of guidelines in the application of the technique in the field of Behavioural Information Security. Hence, this paper aims to provide a comprehensive guide of using PLS-SEM in disclosure and privacy studies on Social Network Sites (SNSs). Data has been gathered using papers (n=21) published between 2006 and 2022 from scholarly databases such as Google Scholar, Association for Information Systems eLibrary (AISeL), IEEE Xplore and Science Direct. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA 2020) was used to analyse and synthesize the status of the field. Our systematic review covers data characteristics, reasons for using PLS-SEM, the evaluation of measurement models, the evaluation of the structural model and reporting best practices. The review proposed guidelines for the use of PLS-SEM in the discipline of Behavioural Information Security with a focus on disclosure and privacy on SNSs studies and other fields as well.
Shah B.A., Zala L.B., Desai N.A.
2023-05-01 citations by CoLab: 6 Abstract  
Mode Choice preference of each individual commuter depends on a number of factors. The classic models for choice estimation have majorly focused on the quantifiable variables such as travel cost, travel time, socio-economic characteristics of riders, trip characteristics, and mode characteristics. This paper aims at analyzing the hidden impact of latent variables integrated with observed variables on mode choice attitude of a rider for an integrated public transport system with environment-friendly feeder mode. The study is in a tier II type metropolitan city of Vadodara, Gujarat. For the purpose a new class of model, Integrated Choice and Latent Variable (ICLV) model is introduced. It integrates the Structural Equation Modelling (SEM) through Analysis of Moment Structures (AMOS) approach for the analysis of latent variable with the classic type choice model analyzed through Biogeme regression. The study precisely captures the attitude of a rider towards the need for comfort and convenience, safety and security, services and facilities, and riding attraction and quality class of latent variables. 26 of initially considered 41 latent variables clubbed into four latent constructs through Confirmatory Factor Analysis (CFA) and SEM approach were incorporated in the ICLV analysis. The results explain the riders’ attitude driven choice for comfort and convenience and service and facilities over the safety and security and riding quality aspects of the mode. The shift demand governed by these latent variables helps to develop a methodological framework, which sets up a base for transport system design oriented policies’ implications as future scope of the research.
Zhou H., Dorsman J.L., Mandjes M., Snelder M.
2023-03-01 citations by CoLab: 11 Abstract  
Nowadays, many cities are intending to reduce the use of private vehicles. Governments are incorporating new mobility services and are adapting their parking policies to promote a more sustainable mobility, as both strategies are believed to have the potential to reduce private vehicle use. To understand the effects of these strategies, one needs to be able to model complex travel behaviour up to a very high level of detail. Owing to their flexibility, robustness and ability to model travel activity behaviour on an individual level, activity based travel demand models (ABM) offer a highly suitable methodology for this purpose. In this paper, we employ this methodology to perform a case study in a metropolitan region in the Netherlands which surrounds and includes the cities of Rotterdam and The Hague. This region is of vital economic importance and has a very developed and dense road network. The population of this region is growing, which motivates the ambition to improve its accessibility and move towards sustainable mobility. Therefore, the findings of this study are important to similar regions seeking to do this as well. After setting up a suitable, calibrated ABM able to perform a comprehensive study on the effects of new mobility services and parking policy adaptations in the above-mentioned region, we design seven scenarios to give quantitative answers to policy-related questions on how altering features can reduce the extent to which private vehicles are used for travelling. These features include the availability of mobility hubs (hubs on neighbourhood level where sustainable travel modes are linked), the availability of car/bike sharing services, the availability of ‘Mobility as a Service’ (MaaS) subscriptions, the amount of parking capacity in the region and the parking costs. We also study what the impact would be of an improved public transport service with lowered public transport travel times to and from the city centers, and the impact of an improved cycling network infrastructure with significantly lowered travel times for bike and e-bike travellers. Based on the case study, we find that the introduction of mobility hubs alone has limited impact. However, combining this with making sharing services available to the public through MaaS subscriptions, there is a potential to reduce the number of car trips significantly, while the number of trips undertaken by a more sustainable (shared) e-bike increases as well as the number of so-called multi-modal mode trips (trips undertaken by a combination of various modes). Furthermore, improving the public transport service and micromobility network further increases the potential of mobility hubs in terms of making mobility more sustainable. The case study also shows that limiting parking capacity and increasing parking costs in the city centers is especially helpful for the reduction of vehicle use, leading to an improved car flow.
Delponte I., Costa V.
2023-02-22 citations by CoLab: 1 Abstract  
Making public transport more flexible, sustainable and efficient has been one the main goals of the last decades for Public Administrations in order to improve urban performances in mobility sector, that is responsible for a big share of pollutant emissions and deeply affects quality life level. Anyway, recently, attention grew on the fact that this topic does not belong to urban areas only and needs tailored measures to be effective: accessibility for peripherical and scarcely populated areas represents the pre-requisite of citizenship rights itself. Basic services (health, education above all) are getting more and more concentrated in order to reduce costs and this means that non-urban residents have to make long trips to reach them. Public Transport itself has become no longer sustainable in these territories because of the small population and low-density levels of transport demand (the so-called “low-demand areas”). That is the reason why flexible and customizable solutions (Demand Responsive Transport-DRT, for instance) could meet the needs of these remote inhabitants, thus improving social inclusion and being the first step to more complex regeneration processes. Italian National Internal Areas Strategy (SNAI) focuses on mobility actions, too. Many flexible transport services have been proposed in order to balance accessibility rights of local residents and economical and environmental sustainability of the service itself. This paper presents the Ligurian Internal Areas experiences (and specifically Antola-Tigullio strategy), where DRT services implementation is currently taking place to tackle marginalization process: referring to these areas non-traditional transport services allow to cover larger areas and longer parts of the day, without adding new costs (service is active only when users need it), thus developing a new mobility scheme.
Adolphson M.
2022-12-01 citations by CoLab: 3 Abstract  
The possibility of attaining environmental and social goals through urban and regional planning has long been the subject of research and debate. The current research investigates the precise relations between urban morphology, lifestyles, social-psychological aspects and work-related travel behaviour in terms of travel distance and travel mode. The study area is the Stockholm region. Travel distance and mode were linked to explanatory variables by linear and multinomial regression methods. Results from this study in the form of marginal effects show that urban morphology and demographics have a substantial influence on travel behaviour. However, lifestyles, attitudes and ideologies have significant influence as well. Travel distance is foremost influenced by attitude to travel distance and occupation. Travel mode is foremost influenced by distance to public transport facility and gender. Urban morphology, a designer lifestyle and ideological concerns regarding ecology matter as well. Thus, sustainable travel behaviours can be promoted by spatial planning. As other factors – attitudes, lifestyles and ideologies – also have a substantial influence, the possibilities and limitations of planning to contribute to a sustainable society should be further debated and if possible – clarified.
Fattah M.A., Riad Morshed S.
2021-06-01 citations by CoLab: 13 Abstract  
The key and fundamental aspects of long-term sustainable urban development are to ensure a sustainable transport system and mobility. The study assessed the sustainability of the transportation system through using the Emissions and Bio-capacity Index (EBI) approach for a developing city, named Khulna City Corporation which has different public transport modes. Vehicular CO2 emissions, carbon uptake land, and biocapacity of fourteen traffic nodes were estimated for identifying the responses of existing landforms to vehicular CO2 emissions. To calculate net CO2 emissions at specified traffic nodes, traffic volume, fuel-use types, and vehicle travel distance data were utilized. The bio-capacity of the land covers of the selected nodes to absorb vehicular CO2 emissions was calculated by GIS-based Remote Sensing methods. Total vehicular CO2 emissions have been calculated 30232.60 tons/year where 50.71% emits from Mahindra. Six of the fourteen nodes had very lower EBI values, corresponding to a higher level of CO2 emissions and low biocapacity which have been considered unsustainable as future traffic nodes. The use of vehicles capable of carrying fewer people, excessive trip generation, inadequate public transport options, narrow road-width, and declination of bio-productive areas are found mainly responsible for unsustainability. The recommended policies will help the urban managers and policymakers to build a sound and sustainable urban environment by controlling emissions.
Feilzer J., Stroosnier D., Dugundji E., Koch T.
2021-05-18 citations by CoLab: 2 Abstract  
Modeling the mode choice by an individual is a challenging task. In this paper, vehicle choice of lessees is discussed. Prediction of vehicle choice occurs by fitting three different logit models: standard, nested and cross-nested multinomial logistic regression. Both nested and cross-nested logit relax error term distribution assumptions and therefore allow for correlations across alternative vehicle choices. It is shown that allowing for correlation across alternatives is the proper way of modeling lessees’ vehicle choice.
Tang X., Wang D., Sun Y., Chen M., Waygood E.O.
Journal of Transport Geography scimago Q1 wos Q1
2020-12-01 citations by CoLab: 31 Abstract  
The social and economic growth as result of promoting the rapid development of tourism in China has brought tremendous pressure on the urban transportation systems. Research of travel behavior concerning the characteristics of tourists has provided effective information for transportation planning. Due to different city plans, public transportation system design, car parking design and management, etc., the local situation in developed countries differs from the counterpart in China. However, little research has studied the factors influencing the choice of travel destinations in tourism. The research aims to study the tourism destination and mode choice behavior of tourists and provides suggestions to improve tourism transportation service system. An online questionnaire survey is used to collect data including the travel characteristics and personal attributes of local tourists in different holidays in Hangzhou, China. A multinomial logit model is constructed with the trip destination set as the dependent variable. Results show that age, residential type, car ownership, companion type and holiday length have a significant impact on destination choice. To determine what influences modal choice for such trips, a second logit model is established with travel mode set as the dependent variable with the explanatory variables of age, gender, companion type, car ownership, holiday length and travel destination found to be significant. The results demonstrated that people aged 26 to 44 prefer suburban areas, and they are the main group driving to their travel destination. Public transport use frequency decreases when the destination is located outside of the main tourist area. Finally, suggestions have been proposed to mitigate the congestion and parking problem based on model analysis from the perspective of the bus line setting, transfer improvements, and the policy to limit cars, respectively.
Thanh Truong T.M., Ngoc A.M.
2020-09-15 citations by CoLab: 17 Abstract  
The objectives of this study are to investigate parking behavior and possible impacts of parking management measure on travel alternatives, then giving the recommendation for transport authorities to achieve the sustainable development of urban transport. To achieve these objectives, the following tasks are addressed. The study firstly gives a basic understanding of factors influencing mode choice, parking location selection, and destination choice. It also highlights the significant role of parking pricing on transport demand management based on international experience. Secondly, parking behavior is investigated in terms of parking location preference, illegal parking phenomenon, and parking duration. Finally, multinomial logit models are developed to estimate the probabilities that transport users who currently drive their private vehicles might choose to use their current mode, change to use the bus, or change to walk for work trips under two scenarios of parking fee increase and bus accessibility improvement. The results of the study might be useful for developing effective parking policies in motorcycle-dominated cities.
Wang Y., Wang Y., Choudhury C.
2020-08-01 citations by CoLab: 15 Abstract  
Studies of travelers’ response behavior to transportation demand management is receiving substantial attention among researchers and transport operators in recent years. While previous studies in this area have generally assumed that the sensitivity of travelers to different factors is homogeneous and relies on survey responses, which may be prone to self-reporting errors and/or subject to behavioral incongruence. Relying on naturalistic data, this paper aims to investigate the behavioral response to pre-peak discount pricing strategy in the context of the Beijing subway with a special focus on the heterogeneity among the travelers. Anonymous smart card data from 5946 travelers before and after the introduction of a peak avoidance policy in Beijing are used to construct a latent class choice model to capture the sensitivity to different factors and the associated taste heterogeneity of travelers. Given the passive nature of the data, the model can offer more realistic outputs. The results indicate that there is substantial heterogeneity in travelers’ responses to the peak avoidance policy, and that they can be probabilistically allocated to four latent classes. For all classes of travelers, the decision to shift their departure to off-peak is affected by the monetary saving, the required change in departure time and the frequency of travel, but in different magnitudes. In particular, only two classes of travelers (who exhibit lower standard-deviation in pre-intervention departure time) show significant sensitivity to price changes indicating that the discount policies are more likely to be effective for these groups. The rest of travelers are largely price insensitive – warranting the need for non-monetary incentives as opposed to fare discounts. To the best of our knowledge, this study is the first to innovatively apply the LCC framework to analyze travelers’ heterogeneous behavior using large-scale smart card data without socio-demographic information. The findings can provide guidance to the subway authority in devising differential peak avoidance policies targeted for different groups of users, which are likely to be more effective than the current ‘one size fits all’ approach.

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