Actual Mode Choice Research Articles

Does emphasis change in transportation mode choice affect workers’ actual mode choice? Implications from Japan in the COVID-19 era

Although modal shift from private motorized vehicles to public and active transport is regarded as crucially important for a sustainable society, such a shift has not been successful in Japan. One reason may be that measures have not satisfied the latent factors underlying people's transportation mode choices. Moreover, these factors may have changed during the COVID-19 pandemic. This study is aimed at ascertaining what workers have emphasized in transportation mode choice, and how those emphases have affected their actual mode choice. We also examined how changes in individuals' emphases during the pandemic have affected their actual mode choices. We used a four-time panel survey with 1377 respondents from Japan that asked participants about important items related to their transportation mode choice and activity patterns at four time points before and during the COVID-19 pandemic. After conducting a factor analysis to ascertain the latent factors behind mode choice, we applied a logistic regression model showing whether or not the respondents used each transportation mode at each time point. A conditional logistic regression model with individual fixed effect was applied to the relationship between an individual's change in emphasis and actual mode choice. Factor analysis results indicated four latent factors: usability and reliability, personal time–space, attitude toward the environment and health, and ease of use and convenience. A higher emphasis on personal time–space encouraged car use and discouraged public transport use at any time points. This trend became stronger during the pandemic. Changes in the emphasis level of this factor for an individual also affected the actual mode choice. A higher emphasis on usability and reliability also discouraged public transport use. Ease of use and convenience encouraged public transport use, and attitude toward the environment and health neither encouraged nor discouraged actual mode choice at any time point. Emphases related to transportation mode choice changed over time. However, changes in individuals' emphasis altered the actual mode choice at some time points but not at others. These results should be considered in transportation planning in order to prompt desired modal shifts by transportation users.

Challenges in Behaviour Modelling of Mode Choice Model - A Peek into Indian Scenario

Mode choice model is one of the crucial steps in the process for Transportation demand modelling. It fore-tell the share of trips attracted to public transportation. Mode choice models compacts very closely with the human choice making behaviour and this continues to attract researchers for further exploration of individual choice making process. The objective of this paper is to observe keenly on the challenges that a modeller will face in Indian scenario. A variety of models are available for prediction. But with the close review it is observed that all these models work either at aggregate level or disaggregate level which works on certain assumptions. This is definitely not going to reflect the actual mode choice behaviour. The particular characters that makes a difference from the world scenario discussed in this paper are diversity in decision making of individual, diversity in socio-economic characteristics, pride and prejudices in mindset that affect the false representation of data, concept of ridesharing and the inhibition in acceptance of the same, travel distance and mode availability in urban and rural scenario. It can be concluded that selecting a model that depict the true nature of commuter is a challenging process. The well-known models available can be trained and calibrated to suit to the need of Indian scenario. Use of machine learning and data mining could be a very useful tool in this model building as all the required changes can be incorporated efficiently

Understanding Young Commuters’ Mode Choice Decision to Use Private Car or Public Transport from an Extended Theory of Planned Behavior

The research examines young commuters’ (age 18–25 years) decision-making process in choosing a mode to commute. The study presented here characterized young commuters’ travel decisions in relation to choosing to use a private car or public transportation for commuting travel. To contribute to greater understanding, the theory of planned behavior (TPB) was used to investigate commuting mode choice, particularly from a social-psychological perspective. Disaggregated travel data was collected from an in-depth survey of young commuters ( n = 3171) who lived in inner and metropolitan Melbourne, Australia. Respondents were clustered based on their usual commuting mode (private car or public transportation). The questionnaire was designed to capture information on young commuters’ attitudes toward their commuting mode, social environment, and travel behavior. Linear regression analysis and binary logistic regression were used to predict intention to choose a commuting mode and the actual mode choice, respectively. Results suggest that young commuters who used a private car held a positive attitude toward the mode. On the contrary, public transportation users had few positive beliefs about commuting by public transportation. Convenience and flexibility were the most valued advantages that the private car offers as a commuting mode. For public transportation users, reliability of the commuting mode was more important than other factors, but they did not agree that public transportation provides reliability. The paper includes a discussion on how the implications of these results can influence government policies and strategies in an effort to increase commuting by public transportation.

Spatiotemporal Analysis of Competition Between Subways and Taxis Based on Multi-Source Data

Excessive competition between taxis and subways has eroded the advantages of public transit systems such as worsening road traffic congestion and environment. This study aims to improve the appeal of subways by a comprehensive understating of competition between taxis and subways. We investigate competitive relationship between these two transportation modes by using empirical multi-source data. First, non-negative matrix factorization (NMF) algorithm is used to discover the spatiotemporal travel patterns of subway-competing taxi users (SCTUs). Second, we propose a new index to quantify the competitiveness of subways based on the actual mode choices results. Then, we reveal the spatiotemporal heterogeneity of competitiveness from perspective of subway network. Taking Beijing, China, for a case study, we extract a week’s worth of GPS records on taxi trajectory and smartcard data of subways. Subway-competing taxi trips (SCTTs) account for the largest proportion of the total taxi trips. As a result, three basic patterns are found in SCTTs. Subway station pairs with high and less competition are divided according to competitiveness index. Among low competition station pairs, three spatial structures are observed, including low-competition collinearity corridors, radial communities, and links between paralleled subway lines. Combining the distribution results of travel pattern and competitiveness degree, short-term and long-term planning suggestions are recommended respectively for station pairs with high demand but low competitiveness and those with low demand and low competitiveness. These findings provide useful insights into promoting more effective and sensitive policies to balance the competition and attract more taxi passengers to the subway system.

Substitution effect or complementation effect for bicycle travel choice preference and other transportation availability: Evidence from US large-scale shared bicycle travel behaviour data

Abstract Among all transportation modes, how do people choose their strategy when commuting? To better understand travel behaviour in new era, we introduce the perspective of “Multi-Choice” to complement that of existing “Single-Choice” based on the random utility maximisation theory and focus on actual travel data from the Pronto! system in Seattle in 2015, to test such a theory as well as other geographical and demographical data. By using mixed multiple regression, we find that at the peak of weekday use, the accessibility of other transportation modes (quantified by their density of infrastructure) could affect the departure flow of the Pronto! stations around them (within a 0.5 km buffer), but in a different trend in terms of multi-choice process. Besides those, we also find that the density of the points of interest around the station could positively affect departure flows on weekends, while the traffic-related factors did not. The current study broadens the traditional perspective of travel demand models by introducing a multi-choice option, and testing it against actual mode choices in people's daily behaviour using shared-bicycle data from Pronto!, Seattle.

Willingness-to-pay for a bus fare reform: A contingent valuation approach with multiple bound dichotomous choices

The aims of this study are twofold: to measure travelers’ willingness to pay (WTP) for bus travel under various travel distance for performing a bus fare reform, and to evaluate the reliability and validity of contingent valuation approach of dichotomous choice with multiple follow-up questions (DCm). To achieve so, this study designs triple-bound dichotomous choice contingent valuation scenarios, and employs multilevel interval regression to capture possible endogeneity within individuals. The estimated models using data with all three bounds, with the first two bounds, and with any specific single bound mostly gave consistent parameter significances and effect directions. However, the WTP estimated using the single third bound model demonstrated a different pattern from the other models, suggesting possible weariness effects. The analysis results also revealed yea-saying and free-riding effects, implying that respondents tended to say yes if their first two responses were yeses, and say no if their first two responses were noes. The yea-sayers had high income and low frequency in using public transit. On the other hand, the free riders significantly less supported the bus fare reform. Under well control of bound and path effects, WTP estimated by the proposed models was consistent with the WTP estimated with actual mode choice data, implying an anchor effect of current stage-based bus fares on travelers’ WTP for future distance-based bus fare scheme. This study suggests that researchers who use DCm to evaluate WTP should investigate internally inconsistent responses caused by psychological and technical factors; DCm provides robust WTP estimates if the survey has been carefully designed with potential bound and path effects well controlled. More importantly, those internally inconsistent responses also provide information that is useful to fare reform.

Commute responses to employment decentralization: Anticipated versus actual mode choice behaviors of new town employees in Kunming, China

This study examines workers’ mode-choice responses to a typical job decentralization policy implemented in China’s urban development – government job relocation (GJR) to new towns in the urban periphery. Broadly, the literature suggests that job decentralization tends to increase car commuting; however, little is known about the effects of China’s GJR initiatives on individuals’ commuting mode choices. Using Kunming as a case study, this study examines how workers’ commuting mode choices have shifted in response to the GJR policy. Our study analyzes two travel survey datasets that span the job relocation process: (1) stated preference (SP) data on workers’ anticipated mode choices after a move of workplace to a planned new town; and (2) revealed preference (RP) data on workers’ actual choices of commuting mode after their jobs were moved. The findings suggest that after job relocation, workers’ actual commuting modes shift from more sustainable modes towards cars. The determinants of workers’ mode choices differ substantially between the hypothetical and actual setting of job relocation. The anticipated mode choices are largely determined by socio-demographic characteristics whereas the actual mode choices are strongly influenced by travel time and housing locations. The evidence from this study offers two important implications for future planning practice of job decentralization. First, planners and policy-makers should be skeptical about the transportation benefits of job decentralization. Second, while SP surveys can assist planners to predict individuals’ mode-choice responses, the robustness of SP results should be carefully assessed before translating into the evidence base for informing job decentralization policy-makings.

Modelling the Propensity in Adhering to a Carsharing System: A Behavioral Approach

In this paper carsharing behavior was investigated with regard to a different and little investigated aspect of users’ behavior: modeling the propensity in adhering to a carsharing system. The propensity was modeled within the random utility framework through starting from a stated preferences survey. The main focus was on the investigation and estimation of a set of attributes able to interpret and measure the propensity. In particular, together with socio-economic and activity related attributes, the satisfaction variable (expected maximum utility) was tested in order to interpret the interest towards carsharing in light of the level of service supplied by the other transport modes and of the users’ socio-economic and activity-based characteristics. The satisfaction variable was specifically calibrated on actual mode choice behavior starting from revealed preferences data.

The effect of psychological traits on mode choice behaviour: an application to a new water transit system in Seoul, Korea

In this paper, we use revealed preference (RP), stated preference (SP) and attitudinal survey data to analyse the behaviour changes caused by a new water transit system on the Han River in Seoul, Korea and to identify the effects of psychological traits on mode choice behaviour. The results confirm that conventional variables, such as individual, household and mode attributes, are significant for mode choice, and that the latent variables, including water transit preference, environmental preferences, comfort and attitudes towards driving and haste, are also very important. In addition, by comparing the estimated scale parameters among a number of scenarios, we also observed the additional impacts of these effects. The latent traits had a more substantial impact on actual mode choice behaviour than on hypothetical behaviour. We systematically captured the taste variation with respect to travellers' latent traits, finding that these significantly reduce or increase the disutility produced by a travel time or cost increase. This heterogeneity was also confirmed in the different willingness-to-pay (WTP) measures at different levels of each latent trait.

Modelling User Mode Choices by an Ellipsoidal Fuzzy Approach

Among transport-related choices one of the most important and studied is the travel mode choice. In fact, the estimation of the travel mode percentages is crucial to forecast possible configurations of the transportation system according to suitable policies. In this work, the travel mode choice is studied by using a fuzzy approach. The underlying idea is that user travel behaviour is intrinsically uncertain and ambiguous and the user choices can be predicted only to some extent. The fuzzy approach aims at identifying the most important variables affecting user’s mode choices and predicts mode choices on the basis of fuzzy similarities approach based on ellipsoidal rules and neuro-fuzzy tuning procedure. The procedure has been tested by using a large database concerning actual mode choices outperforming other conventional fuzzy systems exploiting generalized network-based fuzzy inference.

Does the Academic Rank Matter? Study on the Trip Preferences of Academicians from Different Ranks Employed at Istanbul Technical University

This study estimates a stratified multinomial logit mode choice model of the trip preferences of academicians employed at the Ayazaga campus of Istanbul Technical University. The mode choice model contains three alternatives that are dominantly preferred among academicians: private vehicle, public transport, and service vehicle modes. The data are obtained from a face-to-face questionnaire distributed to a randomly selected number of academicians working on campus. The estimated model is used for a simulation study that aims to understand the differences in modal preferences based on academic ranks and for a scenario analysis to observe the attitudes of the private vehicle users under policy changes. According to the assessment of the analyses, among academician groups of different ranks, different tendencies mostly related to income and age are recognized for actual mode choices, whereas similar approaches prioritizing convenience are noticed under suggested policy changes.

Dynamic Mode Choice Models Considering Unobserved Heterogeneity Based on Mass Point Approach

Travel behaviour is variable across individuals and changeable over time. The objective of this study is to propose dynamic mode choice models dealing with unobserved heterogeneity and state dependence simultaneously based on Mass Point (MP) approach. Besides, dynamic MP models which incorporate the effects of state dependence in different forms are compared with one another regarding the estimative power for the actual mode choice behaviour and the temporal transferability of the models. Three kinds of variables representing the effects of state dependence are introduced in the models: previous choice result, previous choice utility and binary values transformed with the previous choice probability. As a result, it was confirmed that state dependence is significantly effective in mode choice choice models. The dynamic MP model which had previous choice result showed the highest goodness-of-fit of all models. Furthermore, the temporal transferability of these models was statistically accepted.