Influence of pricing on mode choice decision in Jakarta: A random regret minimization model

To reduce traffic congestion, the Government of Jakarta is planning to implement electronic road pricing (ERP) for commuters who pass through arterial roads in Jakarta’s CBD area. This paper studies the implementation of ERP, which in this study is called contribution cost, by utilizing the recently introduced alternative choice model approach called random regret minimization (RRM). In RRM when deciding, an individual is assumed to minimize anticipated regret as opposed to maximizing the utility. A stated preference (SP) survey has been conducted with 507 respondents. Four alternative modes (public transport, park and ride, car, and motorcycle) were presented with several attributes such as travel time, travel cost, waiting time, transfer, parking cost, and contribution cost. The SP survey was divided into two parts, Model 1 with all attributes including contribution cost, and Model 2 with only travel time and travel cost (without the contribution costs). In total 6003 observations for 12 scenarios in Model 1, and 4011 observations for 8 scenarios in Model 2 were obtained. Comparing model fit and prediction accuracy, Model 2 outperforms Model 1. Regarding the value of travel time savings (VTTS), it appears that the incorporation of contribution cost (and other attributes) results in substantially higher VTTS for Model 1 compared to Model 2. Finally for demand elasticities are larger than one for public transport, park and ride and car travel time. The results also show that car contribution cost elasticity is substantially higher than motorcycle contribution cost elasticity

Context-dependent models versus a context-free model: A comprehensive comparison for Swiss and German SP and RP data sets

The random regret minimization (RRM) model considers the relative performance of the alternatives and is therefore context-dependent. In RRM, an individual, when choosing between alternatives, is assumed to minimize anticipated regret as opposed to maximize his/her utility. There are three variants of RRM, the classical CRRM, the μRRM, and the P-RRM. There is also a further approach called relative advantage maximization (RAM). We compare multinomial logit with the four mentioned alternatives. We use stated choice data sets which include mode choice, location choice, parking choice, carpooling, car-sharing. We compare the performance of those five models by their model fit, values of travel time savings (VTTS), and elasticities. Looking at the model fit, RAM outperforms the other models in five cases, whereas the PRRM does so in two cases and μRRM only for one case. The VTTS and elasticities vary substantially which is relevant for cost- benefit analysis or simplified modelling approaches

Understanding Travel and Mode Choice with Emerging Modes: A Pooled SP and RP Model in Greater Jakarta

Research presented in this paper analyzed two data sets from Revealed Preference (RP) and Stated Preference (SP), obtained with a new travel diary and mode choice survey. This survey, called Mobility Jakarta, combines both revealed and stated preference parts and was conducted in the Greater Jakarta region. This is the first survey that collected responses from a substantial sample of the population across the whole metropolitan area. We estimated the discrete choice model using pooled SP and RP data sets and answer several questions regarding people’s behavior on mode choice alternatives. We explored their Willingness To Pay (WTP), e.g., the Value of Travel Time Savings (VTTS), Value of Travel Time Assigned to Travel (VTAT), and the elasticity for all mode choice alternatives, including On-Demand Transport (ODT) and Urban Air Mobility (UAM)

Comparison between RUM, RRM variants, and RAM: Swiss SP and RP data sets

When facing several alternatives, people are often assumed to choose the alternative which maximizes their utilities. This concept is widely known as random utility maximization (RUM). In transportation research, one of the most famous modeling techniques based on this idea, e.g. for modeling mode choice, is the multinomial logit (MNL) approach. Recently there is a growing interest in an alternative modeling approach, random regret minimization (RRM). In RRM, an individual, when choosing between alternatives, is assumed to minimize anticipated regret as opposed to maximize his/her utility. There are three variants of RRM, the classical CRRM, the μRRM, and the P-RRM. There is also another alternative approach called relative advantage maximization (RAM) turning the idea around and focusing on the gains. We compare MNL with the four mentioned alternatives. The data used are stated choice data sets collected by the IVT, ETH Zurich which comprise of mode choice, location choice, parking choice, carpooling, car sharing, etc experiments. We compare the performance of those five models by their model fit (Final LL, hit rate, and prediction). We also present a comparison of their VTTS, travel time and cost elasticities

Context-dependent models comparisons: Swiss and German SP, RP data sets

When facing alternatives, people are often assumed to choose the alternative which maximizes their utilities. This concept is widely known as random utility maximization (RUM). In transportation research, one of the most famous modeling techniques based on this idea, e.g. for modeling mode choice, is the multinomial logit (MNL) approach. Recently there is a growing interest in an alternative modeling approach, random regret minimization (RRM). In RRM, an individual, when choosing between alternatives, is assumed to minimize anticipated regret as opposed to maximize his/her utility. There are three variants of RRM, the classical CRRM, the -RRM, and the P-RRM. There is also a further approach called relative advantage maximization (RAM) turning the idea around and focusing on the gains. We compare MNL with the four mentioned alternatives. The data used are stated choice data sets collected by the IVT, ETH Zurich which comprise of mode choice, location choice, parking choice, carpooling, car-sharing, etc experiments. We compare the performance of those five models by their model fit (Final LL, hit rate, and prediction). We also present a comparison of their VTTS, travel time and cost elasticities

Analyzing commuters’ behavior on egress trip from railway stations in Yogyakarta, Indonesia

Background: Prambanan Ekspres Railway is known as one of the commuting modes in Yogyakarta, Indonesia. Sufficient egress modes do not support this railway. Due to lack of urban mass transit facilities, the commuters independently utilize a reliable mode for their mobility, for instance by owning a motorcycle and using overnight parking service facility in their non-home-station. Objective: This paper aims to understand the commuters’ behavior on their egress trip when they decide to use the train as their main mode. Methods: A direct interview survey on the train was conducted during peak hours from Monday to Friday. By implementing stated preference survey, a logit model was used to analyze mode choice decision from the railway station to activity end destination. Results: The results indicate that walking distance to the parking area and bus-waiting time have a more significant impact compared to the walking distance to bus stop and in-bus travel time. Furthermore, the high cost of overnight parking also significantly influences the decision of choosing an egress mode. Otherwise, egress trip cost has less significance to encourage commuters’ to shift to bus mode

Exploring willingness to pay of urban air mobility and on-demand transport: A pooled SP and RP mode in Greater Jakarta

Research presented in this paper analyzed two data sets from Revealed Preference(RP) and Stated Preference (SP), obtained with a new travel diary and mode choice survey. This survey, called Mobility Jakarta, combines both revealed and stated preference parts and was conducted in the Greater Jakarta region. This is the first survey that collected responses from a substantial sample of the population across the whole metropolitan area. We estimated a pooled SP and RP data sets using a mixed logit (MXL) model and a multinomial logit (MNL) model. We explored their Willingness To Pay (WTP), e.g., the Value of Travel Time Savings (VTTS), Value of Travel Time Assigned to Travel (VTAT), and the elasticity for all mode choice alternatives, including On-Demand Transport (ODT) and Urban Air Mobility (UAM)

Identifying the relationship between parents' and child's car attitudes: For long-term management of car ownership

Most research on individual car ownership decision have always asked an individual about their attitudes and norms. Mostly those questions are focused on perceived expectation of others instead of asking the significant others whether they do influence the individual him/herself. In this research, we explore whether the significant others, in this case, parents, influence the decision of students to buy a car or not. We collect data by finding sets of respondents which consist of father, mother and the child. All three answer questions on attitudes towards car ownership. In Japan, for the pilot study, we have collected 300 sets of respondents. We found that the parents’ car attitudes and the respect for their parents strongly influence the attitudes of the children. We also found that mother attitudes toward the car are overall less positive than those of the fathers. However, mother attitudes can explain the child’s attitude significantly better than father attitudes. This suggests that possibly influencing mothers’ attitudes will also influence the children in the long term. Other potential future work, is to compare attitudes of parents and possibly significant others in different countries. Since different context might have different social norms that influence person’s behavioral intention