Analysis of Travel Time Saving Benefit by Understanding Individual Needs and Value of Activity Time: Case Study of Tokyo and Jakarta

2003 ◽  
Vol 1854 (1) ◽  
pp. 12-21 ◽  
Author(s):  
Irwan Prasetyo ◽  
Daisuke Fukuda ◽  
Hirosato Yoshino ◽  
Tetsuo Yai
Keyword(s):  
Travel Time ◽  
Time Allocation ◽  
Choice Model ◽  
Stated Preference ◽  
Revealed Preference ◽  
Psychological Needs ◽  
Activity Time ◽  
Time Saving ◽  
Allocation Model ◽  
Preference Data

Quantification of the value of time (VOT) is important for measurement of the benefit of transportation projects in terms of travel time savings. In Japan, VOT is considered higher on weekends than on weekdays because on the weekend people have limited time to allocate to discretionary activities that are not normally done on weekdays, such as family care-related activities. In Indonesia, a culturally diverse country, providers and users seem to have different perceptions of VOT. A method of analyzing the value of activity time is presented. It argues that the benefit of travel time saving should be evaluated in more detail on weekends by considering the value of discretionary activities to explain these phenomena theoretically. Activity diary surveys were conducted in Tokyo, Japan, and Jakarta, Indonesia, to verify the influence of psychological needs on people's holiday activities. Finally, a time allocation model that uses the revealed preference data and a marginal activity choice model that uses stated preference data are proposed to calculate the value of activity time. The theories underpinning these models are Maslow's psychological needs, consumer theory in economics, and a discrete choice model. The empirical results show that an individual's priority of needs influences time allocation. In particular, the results show that in Tokyo, spending time with family on weekends is more valuable than other types of activities, while in Indonesia the value of spending time with family exceeds that of work time even on weekdays.

Analysis of Time Allocation, Departure Time, and Route Choice Behavior Under Congestion Pricing

2000 ◽  
Vol 1725 (1) ◽  
pp. 95-101 ◽  
Author(s):  
Toshiyuki Yamamoto ◽  
Satoshi Fujii ◽  
Ryuichi Kitamura ◽  
Hiroshi Yoshida
Keyword(s):  
Time Allocation ◽  
Choice Model ◽  
Stated Preference ◽  
Congestion Pricing ◽  
Route Choice ◽  
Multinomial Logit Model ◽  
Allocation Model ◽  
Departure Time ◽  
Departure Time Choice ◽  
Pricing Schemes

Driver behavior under congestion pricing is analyzed to evaluate the effects of alternative congestion pricing schemes. The analysis, which is based on stated preference survey results, focuses on time allocation, departure time choice, and route choice when a congestion pricing scheme is implemented on toll roads in Japan. A unique feature of the model system of this study is that departure time choice and route choice are analyzed in conjunction with the activities before and after the trip. A time allocation model is developed to describe departure time choice, and a route and departure time choice model is developed as a multinomial logit model with alternatives representing the choice between freeways and surface streets and, for departure time, the choice from among before, during, or after the period when congestion pricing is in effect. The results of the empirical analysis suggest that departing during the congestion pricing period tends to have higher utilities and that a worker and a nonworker have quite different utility functions. The comparative analysis of different congestion pricing schemes is carried out based on the estimated parameters. The results suggest that the probability of choosing each alternative is stable even if the length of the congestion pricing period changes, but a higher congestion price causes more drivers to change the departure time to before the congestion pricing period.

scholarly journals Likelihood of Motorcyclists Transferring to Safer Mode of Transport in Cairo, Egypt

2019 ◽  
Vol 8 (6) ◽  
pp. 2411-2416
Keyword(s):  
Travel Time ◽  
Road Traffic ◽  
Choice Model ◽  
Stated Preference ◽  
Urban Transportation ◽  
Research Work ◽  
Revealed Preference ◽  
Travel Cost ◽  
Mode Decision ◽  
Road Traffic Crashes

Road traffic injuries and mortality are mainly caused by motorcycle crashes. Practically, 50% of people who meet their death in road traffic accidents (RTAs) are motorcyclists. The issue is increasingly articulated in progressing nations where the use of motorcycles has gained popularity in the past decades. Moreover, death and fatalities caused by accidents involving motorcyclists are also in the rise due to the increasing trend. Hence, motorcyclists are encouraged to use alternative modes of transportation that are safer in the attempt to minimise losses. As a result, a policy ought to be created to enhance urban transportation service and control motorcycle proprietorship. The current research that lays the groundwork aims to contribute a more elaborated analysis on motorcycle user mode decision conduct as well as an excellent comprehension of the conceivable efforts that can be taken to support motorcyclists to shift to a safer mode of transportation, particularly bus. In the current research work, the binary logit mode choice model was created for two elective modes in order to distinguish the separate practices of motorcyclists and bus users and assess their reactions to a situation that can minimize both time and expenses involved in bus travel. In addition, it should be noted that this paper surveyed a total of 327 travellers from Greater Cairo Region (GCR) in Egypt, the bus users were identified through revealed preference, while the motorcyclists were identified through revealed and stated preference surveys. In this case, travel time, travel cost, age, sexual orientation, income level, trip purpose, education level, and privacy significantly influence motorcycle user mode decision conduct. The likelihood of motorcyclists to utilize the use of buses was additionally analyzed dependent on a situation of minimized bus travel time and travel cost. These elements are very important in a program that attempts to draw in motorcyclists to utilize public transport, particularly bus. The outcomes can help the process of decision making on all levels in assigning the necessary assets prudently for the advancement of urban transportation services, reduced number of road traffic crashes, and increased road safety. This examination, which is the first of its sort in Egypt, assesses the model choice behaviour for motorcyclists

Large-Scale Application of a Combined Destination and Mode Choice Model Estimated with Mixed Stated and Revealed Preference Data

2017 ◽  
Vol 2669 (1) ◽  
pp. 31-40 ◽  
Author(s):  
Michael Heilig ◽  
Nicolai Mallig ◽  
Tim Hilgert ◽  
Martin Kagerbauer ◽  
Peter Vortisch
Keyword(s):  
Large Scale ◽  
Travel Demand ◽  
Choice Model ◽  
Stated Preference ◽  
Mode Choice ◽  
Revealed Preference ◽  
Demand Model ◽  
Agent Based ◽  
Preference Data ◽  
Mode Choice Model

The diffusion of new modes of transportation, such as carsharing and electric vehicles, makes it necessary to consider them along with traditional modes in travel demand modeling. However, there are two main challenges for transportation modelers. First, the new modes’ low share of usage leads to a lack of reliable revealed preference data for model estimation. Stated preference survey data are a promising and well-established approach to close this gap. Second, the state-of-the-art model approaches are sometimes stretched to their limits in large-scale applications. This research developed a combined destination and mode choice model to consider these new modes in the agent-based travel demand model mobiTopp. Mixed revealed and stated preference data were used, and new modes (carsharing, bikesharing, and electric bicycles) were added to the mode choice set. This paper presents both challenges of the modeling process, mainly caused by large-scale application, and the results of the new combined model, which are as good as those of the former sequential model although it also takes the new modes into consideration.

scholarly journals Do millennials value travel time differently because of productive multitasking? A revealed-preference study of Northern California commuters

2021 ◽  
Author(s):  
Aliaksandr Malokin ◽  
Giovanni Circella ◽  
Patricia L. Mokhtarian
Keyword(s):  
Older Adults ◽  
Young Adults ◽  
Willingness To Pay ◽  
Travel Time ◽  
Choice Model ◽  
Mode Choice ◽  
Revealed Preference ◽  
Northern California ◽  
Factors Affecting ◽  
The Impact

AbstractMillennials, the demographic cohort born in the last two decades of the twentieth century, are reported to adopt information and communication technologies (ICTs) in their everyday lives, including travel, to a greater extent than older generations. As ICT-driven travel-based multitasking influences travelers’ experience and satisfaction in various ways, millennials are expected to be affected at a greater scale. Still, to our knowledge, no previous studies have specifically focused on the impact of travel multitasking on travel behavior and the value of travel time (VOTT) of young adults. To address this gap, we use an original dataset collected among Northern California commuters (N = 2216) to analyze the magnitude and significance of individual and household-level factors affecting commute mode choice. We estimate a revealed-preference mode choice model and investigate the differences between millennials and older adults in the sample. Additionally, we conduct a sensitivity analysis to explore how incorporation of explanatory factors such as attitudes and propensity to multitask while traveling in mode choice models affects coefficient estimates, VOTT, and willingness to pay to use a laptop on the commute. Compared to non-millennials, the mode choice of millennials is found to be less affected by socio-economic characteristics and more strongly influenced by the activities performed while traveling. Young adults are found to have lower VOTT than older adults for both in-vehicle (15.0% less) and out-of-vehicle travel time (15.7% less), and higher willingness to pay (in time or money) to use a laptop, even after controlling for demographic traits, personal attitudes, and the propensity to multitask. This study contributes to better understanding the commuting behavior of millennials, and the factors affecting it, a topic of interest to transportation researchers, planners, and practitioners.

scholarly journals Characteristics Analysis of Freight Mode Choice Model According to the Introduction of a New Freight Transport System

2019 ◽  
Vol 11 (4) ◽  
pp. 1209 ◽  
Author(s):  
Seungjin Shin ◽  
Hong-Seung Roh ◽  
Sung Hur
Keyword(s):  
Travel Time ◽  
Transport System ◽  
Choice Model ◽  
Stated Preference ◽  
Statistical Significance ◽  
Explanatory Power ◽  
Service Level ◽  
Freight Transport ◽  
Transport Cost ◽  
Transport Mode

The purpose of this study is to identify the characteristics of freight mode choices made by shippers and carriers with the introduction of a new freight transport system. We set an area in which actual freight transport takes place as the analysis scope and performed a survey of the shippers and carriers that transport containers to identify their stated preference (SP) regarding the new freight mode. The SP survey was carried out through an experimental design and this study considered the three factors of transport time, transport cost, and service level. This study compared and analyzed the models by distance using an individual behavior model. The results of estimating the model showed that the explanatory power of the model classified by distance and the individual parameters have statistical significance. The hit ratio was also high, which confirms that the model was estimated properly. In addition, the range of elasticity and the value of travel time analyzed using the model were evaluated to be appropriate compared to previous studies. The findings of the elasticity analysis show that strategies for reducing the transport cost are effective to increase the demand for the new transport mode. The value of travel time of freight transport was found to be higher than the current value generally applied in Korea. Considering that the value of travel time currently used is based on road freight transport, further research is required to apply a new value of travel time that reflects the characteristics of the new transport mode in the future.

scholarly journals Railway and road discrete choice model for foreign trade freight between Antioquia and the Port of Cartagena

2016 ◽  
Vol 36 (3) ◽  
pp. 22 ◽  
Author(s):  
Juan Diego Pineda Jaramillo ◽  
Iván Reinaldo Sarmiento Ordosgoitia ◽  
Jorge Eliécer Córdoba Maquilón
Keyword(s):  
Qualitative Research ◽  
Discrete Choice ◽  
Logit Model ◽  
Choice Model ◽  
Stated Preference ◽  
Revealed Preference ◽  
Freight Transportation ◽  
Multinomial Logit Model ◽  
Discrete Choice Model ◽  
The Cost

Most Colombian freight is transported on roads with barely acceptable conditions, and although there is a speculation about the need for a railway for freight transportation, there is not a study in Colombia showing the variables that influence the modal choice by the companies that generate freight transportation. This article presents the calculation of demand for a hypothetical railway through a discrete choice model. It begins with a qualitative research through focus group techniques to identify the variables that influence the choice of persons responsible for the transportation of large commercial companies in Antioquia (Colombia). The influential variables in the election were the cost and service frequency, and these variables were used to apply a Stated Preference (SP) and Revealed Preference (RP) survey, then to calibrate a Multinomial Logit Model (MNL), and to estimate the influence of each of them. We show that the probability of railway choice by the studied companies varies between 67% and 93%, depending on differences in these variables.

Strategic Management of New Products: Ex-Ante Simulation and Market Segmentation

2013 ◽  
Vol 55 (2) ◽  
pp. 289-314 ◽  
Author(s):  
Jae Young Choi ◽  
Jungwoo Shin ◽  
Jongsu Lee
Keyword(s):  
Choice Model ◽  
Stated Preference ◽  
New Products ◽  
Demand Forecasting ◽  
Consumer Preference ◽  
Gaussian Mixture ◽  
Electronic Payment ◽  
Preference Data ◽  
Payment Instruments ◽  
Stated Preference Data

Among various methodologies for demand forecasting of new products, the random-coefficient discrete-choice model using stated preference data is considered to be effective because it reflects heterogeneity in consumer preference and enables the design of experiments in the absence of revealedpreference data. Based on estimates drawn from consumer preference data by structural hierarchical Bayesian logit models, this study develops the overall, strategic, demand-side management for new products by combining market share simulation and a rigorous clustering methodology, the Gaussian mixture model. It then applies the process to the empirical case of electronic payment instruments.

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