Explain Travel Behavior Research Articles

Assessing Non-linear Influences of Urban Layout on Driving Travel Distance: A Mumbai Case Study

Introduction This study investigates the impact of built environment factors on travel behavior in Mumbai, India, focusing on the non-linear effects on driving distances. The rapid urbanization and complex urban of Mumbai constitute present challenges for sustainable transportation, necessitating a deeper understanding of how urban planning influences travel behavior. While demographic factors have often been highlighted in travel studies, this research prioritizes the role of built environment factors. Materials and Methods The study utilized Gradient Boosting Decision Trees (GBDT) to analyze household travel survey data from Mumbai, capturing the non-linear relationships between built environment variables and driving distances. Partial dependence plots were used to visualize these effects, and the relative importance of each variable was assessed to identify key determinants of travel behavior. Results The analysis identified trip time as the most influential factor in determining driving distances, followed by built environment characteristics, such as proximity to commercial areas and intersection density. Socio-demographic factors were found to have a comparatively low impact. Non-linear relationships were observed, such as the stabilization of driving distances beyond certain thresholds of block density and proximity to bus stops. Discussion The findings challenge the traditional emphasis on demographic factors in explaining travel behavior, highlighting the significant role of urban form. The study reveals that specific built environment factors, such as accessibility and connectivity, play a crucial role in shaping driving behavior in a rapidly urbanizing city like Mumbai. These results suggest that urban planning strategies should prioritize these factors to reduce car dependency. Conclusion This study underscores the importance of the built environment in influencing travel behavior in Mumbai, particularly in reducing driving distances. The insights gained offer valuable guidance for urban planners and policymakers aiming to promote sustainable mobility in rapidly developing cities. Further research is recommended to validate and expand upon these findings in other urban contexts.

Study of travel motivation and visit intention: The mediating role of perceived risks and travel constraints

The motivation to travel has been extensively studied, as it plays a crucial role in influencing people's travel decisions. Various theories have been proposed to explain travel behavior, including allocentric, psychocentric, push-pull factors, TPC, and TCL. This study delves into the impacts of perceived risks and travel constraints on Japanese people's motivation to travel to Mongolia, employing the push-pull theory as a framework. In the questionnaire survey, 142 Japanese citizens were selected by simple random sampling method, and the survey was conducted in Japanese and English between April and May 2023. The collected data were analysed using IBM SPSS 26 and SmartPLS 4 software. Out of the seven proposed hypotheses, four were confirmed and three were rejected. When examining risk/constraints as mediating variables, the results revealed that push motivation did not significantly influence travel intention, while pull factors demonstrated a statistically significant relationship. Furthermore, two and three variables were identified to characterize the push and pull factors that drive Japanese people's travel decisions. Two segments of travellers were also identified: those seeking nature-based experiences and those interested in historical and cultural attractions. These findings may guide tourism business operators seeking to attract Japanese travellers to Mongolia.

The Role of Culture Orientation as a Moderation Variable on Visiting Behavior at the World Heritage Site

Indonesia is famous for its diversity of tourism among tourist destinations in Indonesia, some of which have been recognized by UNESCO as included in the list of world cultural heritage sites, such as the Borobudur Temple. The problem that has occurred so far is the lack of concern from millennials towards Borobudur Temple as a tourist attraction marked by a low interest in visiting (Dimyati, 2019). Various efforts have been made, including collaborating with travel bloggers and influencers assisted by Indonesian digital agencies. Its role is to give a good impression of a tourist destination in Indonesia so that it can attract interest to visit, especially the millennial generation (Bernadiaz, 2021). Efforts to increase the interest in traveling to world heritage sites by millennials through various strategies that have been carried out require an empirical explanation of the signification of the results obtained; this study aims to explain the factors that influence millennial behavior in traveling, especially millennial responses to Borobudur Temple tourism objects. Various studies discussing individual behavior towards World Heritage Site (WHS) tourist destinations have been conducted a lot. Some that can be put forward here include Halpeny et al. (2018); Mehmood et al. (2018); See and Goh (2019); Rio et al. (2020); Carreira et al. (2021); Deb and Lomo-David (2021); and Xu et al. (2021). However, there is no universal model explaining travel behavior in all situations and conditions, including cultural tourism at Borobudur Temple. This is what provides an opportunity in this study to design a model that explains explicitly the phenomenon of individual behavior, which is millennials traveling at Borobudur Temple. Keywords: Perceived Destination Quality, Perceived Social Media, Attitude, Intention to Visit, Culture Orientation

Value-Based Approach to Assess the Impact of Lifestyles on Mode Shares

Travel behavior research has long been dominated by a rational perspective considering primarily objective factors such as price, travel time, and speed. Only at the end of the 1990s was attention also paid to subjective factors such as perceptions and attitudes. Since then, a growing number of studies combine objective and subjective factors in explaining travel behavior. This paper adds to this by focusing on the influence of lifestyles on mode share. To this end, an online survey was carried out in Belgium, completed successfully by 334 respondents. Lifestyles were measured based on a psychographic or value-based approach using the Portrait Values Questionnaire (PVQ) developed by Schwartz. Results of a structural equation model (SEM) indicate that using value-based lifestyles adds new insights to the analysis of mode share. Personal values have not only a direct effect on mode share but also an indirect effect because of interactions with urban residential location choices, car ownership decisions, and activity patterns. The findings suggest that public transport use could be encouraged by promoting it as an act of caring for others. At the same time, policy-makers should invest in creating positive experiences for travelers using public transport.

Microscopic activity sequence generation: a multiple correspondence analysis to explain travel behavior based on socio-demographic person attributes

Activity sequencing is a crucial component of disaggregate modeling approaches. This paper presents a methodology to analyse and predict activity sequence patterns for persons based on their socio-demographic attributes. The model is developed using household travel survey data from Germany. The presented method proposes an efficient approach to replace complex activity-scheduling modules in activity-based models. First, the paper describes a multiple correspondence analysis technique to identify the correlation between activity sequence patterns and socio-demographic attributes. Secondly, a probabilistic model is developed, which could predict likely activity sequence patterns for an agent based on the results of the multiple correspondence analysis. The model is predicting activity sequence patterns fairly accurately. For example, the activity sequence pattern home–work–home is well predicted ({mathrm{R}}^{2} = 0.99) for all the workers, and the activity sequence pattern home–education–home is rather well predicted ({mathrm{R}}^{2} = 0.90) for students. The model predicts the 112 most common activity sequence patterns reasonably well, which covers 72% of all activity sequence patterns observed.

A new perspective on the role of attitudes in explaining travel behavior: A psychological network model

• Psychological network models relax the restrictive assumptions of theoretical models of travel behavior. • The convenience of using the car takes a central position in the network. • Between-person and within-person network models show evidence of clustering. • At the within-person level no strong connections between attitudes and behaviors seem to exist. Psychological factors are generally thought to play an important role in the prediction of individual variations in travel behavior and travel related choices. To assess their effects in statistical models, three assumptions are typically made, namely: (1) the psychological factors influence behavior/choices and not vice versa, (2) psychological factors can be conceptualized as latent variables measured by observed indicators and (3) estimated between-person relationships are indicative of within-person relationships. Recent research has shown that each of these assumptions is conceptually and empirically problematic. This paper introduces to the field of travel behavior research an alternative modeling approach which has its roots in the emerging field of Network Psychometrics. This so-called psychological network model avoids the above mentioned problematic assumptions, by modeling the relationships between attitudinal and behavioral indicators as dynamic causal systems which can be operationalized as a network. We illustrate the new insights that may be gained from this approach in a travel behavior context. In particular, we estimate between-person and within-person network models using data from a (two-wave) panel survey containing indicators regarding travel modality use and related attitudes. Our results indicate that the extent to which the use of a mode is considered convenient is most strongly connected to the actual use of the corresponding mode, and that the convenience of using the car takes a central position in the attitude-behavior network. At the within-person level, no strong connections between attitudes and behaviors seem to exist. This latter finding serves as a warning against the practice, embodied in many popular travel behavior models, of interpreting associations between attitudes and (travel) behaviors as causal within-person relations.

Using CyclePhilly data to assess wrong-way riding of cyclists in Philadelphia

ProblemThe increasing use of smartphones and low cost GPS have provided new sources for collecting data and using them to explain travel behavior. This study aims to use data collected from a smartphone application (CyclePhilly) to explain wrong-way riding behavior of cyclists on one-way segments to help better identify the demographic and network factors influencing the wrong-way riding decision making. MethodsThe data used in this study consist of two different sources: (a) Route trips data downloaded from the CyclePhilly Website contained trips detailed up to segment level, collected from May 2014 to April 2016 (12,202 trips by 300 unique users); and (b) Open Street Maps (OSM). Using ArcGIS, we calculate detour routes for each wrong way segment. We then built a mixed logistic regression model to identify the trip and riders' characteristics affecting wrong-way riding behavior. Next, we explore the characteristics of road facilities associated with wrong-way riding behavior. Results and discussionOnly 2.7% of travel distance is wrong-way, yet 42% of trips include a wrong-way segment. Commute trips have a higher chance of wrong-way riding. The longer the trips also include more wrong-way riding. Segments with higher detour ratios (ratio of distance with a detour to the wrong-way distance) are found to be associated with more wrong-way behavior. Compared to roads with no bike lane, roads with sharrow markings and buffered bike lane discourage wrong way riding. Practical applicationsThis study proposes new methods that can be adapted to use naturalistic and probe data and analyze city-wide aberrant riders' behavior. These help planners and engineers choose between various types of bike infrastructure. Wrong-way riding is one application that can be investigated, but probe bicycle datasets provide unprecedented resolution and volume of data that will allow for more sophisticated safety and planning analyses.

A Spatial Latent Profile Analysis to Classify Land Uses for Population Synthesis Methods in Travel Demand Forecasting

In this paper, a new land use classification method is explored for its utility in explaining travel behavior and as a new dimension in population synthesis for travel demand forecasting. This method is based on latent profile analysis applied to 17 business establishment indicators for each of the more than 20,000 block groups in California. The method reproduces the four types of land use environments (urban, suburban, exurban, and rural) identified in a previous paper, and improves our ability to create a finer-grain geographic classification based on land use. It also offers similar indications about the difference between urban dwellers (that make more trips but travel shorter distances) and rural residents (that make fewer trips but with more vehicle miles traveled).

The built environment and travel behavior in urban China: A literature review

Interests in studying of the built environment impacts on travel behavior have proliferated from North America to other parts of the world including China. Until very recently, there has been very little research into travel behavior in China. However, during the last decade, there has been a fast growing interest in studying the built environment and travel behavior in Chinese cities, perhaps motivated by China’s unprecedented urbanization and rapid urban transport development. Case studies from China provide new insights into the impacts of built environment on travel behavior that can help to enrich existing scholarship. However, currently there is a generally poor understanding of the role played by Chinese research and how it has enriched the international literature. This paper aims to fill this gap by reviewing studies in and outside China by both Chinese and non-Chinese scholars. The focus is on the contribution of these studies to the international literature. We identify four areas of contribution: how the built environment has been developed and its implications for travel behavior; the importance of housing sources in defining residential built environment and explaining travel behavior; the unique Danwei (or work unit) perspective on jobs-housing relationships and commuting behavior; and the importance of neighborhood types in explaining travel behavior in Chinese cities. The findings from this review should be relevant for researchers interested in developing future studies that will further advance geographic knowledge of the built environment and travel behavior, specifically in China and with broader global contexts.

Temporal Stability of Generation Choice Models

This paper evaluates the temporal stability of generation choice models by considering two cases. The first case evaluates temporal stability with widely used explanatory variables, and the second examines whether temporal stability improves with the inclusion of life cycle, area type, and accessibility. The results of this research show that generation choice models, with their ability to estimate person trips and accommodate more variables that define the traveler and the trip, are temporally stable for home-based work trips by workers and home-based other trips by nonworking adults. Home-based other trips by workers show mixed results with respect to temporal stability, while home-based other trips by children do not pass the test of temporal stability with any of the measures considered. This research shows that, while life cycle, area type, and accessibility variables help explain travel behavior, they provide little, if any, additional benefit with respect to temporal stability.

Boundedly- and Non-Rational Travel Behavior and Transportation Policy

This paper examines boundedly rational and non-rational travel behavior and their implications for transportation policy. Following Herbert Simon, the paper posits that individual rationality is “bounded” by cognitive capacity, and that affective factors influence decision-making. Its primary aim is to assess how well policy and planning models address such behavior and whether such behavior “matters” in a public policy sense. The paper concludes that it is necessary to incorporate boundedly and non-rational behavior more extensively in travel demand modeling. This could help explain travel behavior patterns that do not usually correspond to the utility maximization paradigm, and assist public policy decision makers in making wiser choices about transportation investment and management.

Review of the concept of travel typologies: The case of Switzerland

The study aims at reviewing the concept of travel typologies. For this purpose the two determination factors explaining travel behavior, motivation and destination choice, are chosen to verify the validity of travel typologies. The study is based on an extensive and representative travel survey covering almost 2,000 households and more than 12,000 trips within Switzerland. Generally, travel typologies seem to be a valuable instrument for the tourism industry to anticipate consumer behavior and to plan marketing activities appropriately. The results reveal that there is no clear and highly significant connection between travel typologies and the selected determination factors. As a conclusion, the concept of travel typologies seems to be not reliable.

Does neighborhood design influence travel?: A behavioral analysis of travel diary and GIS data

Can urban design improve the environment? If communities could be designed to reduce automobile use, then yes. But can urban design influence travel? Surprisingly perhaps, the effects of any specific neighborhood feature on travel behavior at the margin are all but unknown. The policy significance of this issue is reflected in the swelling popularity of the ‘new urbanism’ and other planning strategies employing land use tools to mitigate the environmental impacts of metropolitan development. In addition to asserting that development patterns and densities affect how far, how often, and by what means people travel, urban designers frequently argue that the legibility and shape of the local street pattern play a key role. ‘Connected’ residential blocks are thus associated with less driving by comparison with the circuitous routes of the modern suburban cul-de-sac—chiefly by reducing trip lengths and facilitating pedestrian and transit access. Remarkably, there is little empirical and theoretical support for these claims. This paper provides the first direct tests of these hypotheses within a consistent behavioral framework. An analysis of household travel diary and GIS data for San Diego finds little role for land use in explaining travel behavior, and no evidence that the street network pattern affects either short or long non-work travel decisions. While results may vary in other areas, the empirical argument for using land use as an element of regional air quality or other environmental plans remains to be demonstrated.