Modelling effects of changes in travel time and costs of toll road usage on choices for residential location, route and travel mode across population segments in the Jakarta-Bandung region, Indonesia

Andani, I Gusti Ayu; Puello, Lissy Cesarina La Paix; Geurs, Karst

doi:10.1016/j.tra.2020.12.012

Cited by 14 publications

(6 citation statements)

References 53 publications

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“…To account for preference heterogeneity, we used a mixed logit regression model with random, which defines the choice probability across a sequence of T choices, as shown in Equation ( 4). The random parameter βet in the equation depicts that it varies over respondents, with the density described by f (βet) and is not fixed [33]. The estimation of this model involved the simulation of log-likelihood.…”

Section: Analysis Methodsmentioning

confidence: 99%

“…The results of the multinomial logit regression model and a mixed logit regression model are summarized in Tables 4 and 5, respectively. The mixed logit regression model is regarded as a reliable model for quantifying travel mode or route choice [33]. It has been widely employed in transportation, tourism, and economic studies.…”

Section: Estimated Model Coefficientsmentioning

confidence: 99%

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Exploring the Effects of Carpooling on Travelers’ Behavior during the COVID-19 Pandemic: A Case Study of Metropolitan City

Chen

Liu

2021

Sustainability

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Transportation accounts for more than a quarter of the greenhouse gas emissions that are causing climate change. Carpooling is a subset of the sharing economy, in which individuals share their vehicle with commuters to save travel expenses. In recent decades, carpooling has been promoted as a feasible alternative to car ownership with the potential to alleviate traffic congestion, parking demand, and environmental problems. Unstable economic conditions, cultural norms, and lack of infrastructure make cultural exchange activities and mobility habits different in developing nations to those in developed countries. The rapid evolution of sharing mobility has reshaped travelers’ behavior and created a dire need to determine the travel patterns of commuters living in megacities in developing countries. To obtain data, a web-based stated choice (SC) experiment was used in this study. It used mode-related variables, socioeconomic demographic variables, and a coronavirus disease 2019 (COVID-19) precautionary measure variable. Logit models, namely the mixed logit regression model (ML) and the multinomial logit regression model (MNL), were applied to analyze the available data. According to modeling and survey data, economic variables associated with modes of transport, such as trip time and trip cost, were determined to be significant. Additionally, the results revealed that commuters were more conscious of COVID-19 preventive measures, which was determined to be highly significant. The findings showed that the majority of residents in the COVID-19 pandemic continue to rely on automobiles and motorcycles. It is noteworthy that individuals with more than two members in their family and a travel distance of less than seven miles were more likely to prefer a carpooling service. This study’s findings will provide a basis for researchers to aid existing operators in the field of transportation, as well as offer guidelines for governments in developing countries to enhance the utility of transportation networks.

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Section: Analysis Methodsmentioning

confidence: 99%

Section: Estimated Model Coefficientsmentioning

confidence: 99%

Exploring the Effects of Carpooling on Travelers’ Behavior during the COVID-19 Pandemic: A Case Study of Metropolitan City

Chen

Liu

2021

Sustainability

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“…The number of people using airplanes to travel between cities on Java Island in Indonesia has decreased since the construction of the Trans Java toll road (Irawan et al, 2020). Toll road infrastructure also has an impact on changing people's travel behavior (Andani et al, 2021), as well as increasing trade and investment activities in the areas it passes through (Ardiyono et al, 2018). Hence, the construction of these toll road sections has resulted in an increase in the number of services available on toll roads, such as rest areas, whose service levels are regulated separately through regulations issued by the Indonesian government.…”

Section: Introductionmentioning

confidence: 99%

“…Hence, the construction of these toll road sections has resulted in an increase in the number of services available on toll roads, such as rest areas, whose service levels are regulated separately through regulations issued by the Indonesian government. By July 10 th , 2020, Indonesia had 1,820 kilometers of toll roads built, mostly in Java but also in Sumatra and Kalimantan (Andani et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Factors Affecting Customer Loyalty: An Empirical Evidence from the Toll Road Industry in Indonesia

Irawan,

Alversia

2024

Binus Business Review

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Toll road rest areas are one of the main pillars of the toll road industry, and higher interest in buying at toll road rest areas is one of the keys to their financial success. The research aimed to identify and analyze the relationship between revisit intention and customer loyalty, as well as perceived price fairness, perceived satisfaction, and service quality. These variables were believed to be the main drivers for toll road users to make purchases at toll road rest areas. A statistical analysis approach was used with the Partial Least Square-Structural Equation Modelling (PLS-SEM) method for 573 respondents. They were consumers of the Trans Java toll road rest area. The survey was conducted directly on customers of the Trans Java toll road rest area at 15 locations. The results show that perceived price justice and satisfaction positively and significantly impact revisit intention. Then, revisit intention has a positive and significant impact on customer loyalty. Service quality has a positive and significant impact on perceived satisfaction and customer loyalty. The findings show that service quality, which is most strongly influenced by assurance, responsiveness, and empathy, is the main factor influencing customer loyalty. Based on the research results, the practical application is how managers can improve service quality, perceived price justice, and perceived satisfaction for price-sensitive consumers, who also tend to be sensitive to the service quality they get.

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“…Therefore, researchers have applied other discrete choice models to relax the IID assumption and obtain still more accurate results. In this regard, heteroscedastic extreme value, nested logit, mixed multinomial logit, multinominal probit [ 10 , 14 , 15 ], joint models, hybrid choice [ 16 ], and latent class discrete choice models [ 17 ] have been used to model individual travel mode choice.…”

Section: Introductionmentioning

confidence: 99%

Application of Machine Learning to Child Mode Choice with a Novel Technique to Optimize Hyperparameters

Naseri

Waygood

Wang

et al. 2022

IJERPH

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Travel mode choice (TMC) prediction is crucial for transportation planning. Most previous studies have focused on TMC in adults, whereas predicting TMC in children has received less attention. On the other hand, previous children’s TMC prediction studies have generally focused on home-to-school TMC. Hence, LIGHT GRADIENT BOOSTING MACHINE (LGBM), as a robust machine learning method, is applied to predict children’s TMC and detect its determinants since it can present the relative influence of variables on children’s TMC. Nonetheless, the use of machine learning introduces its own challenges. First, these methods and their performance are highly dependent on the choice of “hyperparameters”. To solve this issue, a novel technique, called multi-objective hyperparameter tuning (MOHPT), is proposed to select hyperparameters using a multi-objective metaheuristic optimization framework. The performance of the proposed technique is compared with conventional hyperparameters tuning methods, including random search, grid search, and “Hyperopt”. Second, machine learning methods are black-box tools and hard to interpret. To overcome this deficiency, the most influential parameters on children’s TMC are determined by LGBM, and logistic regression is employed to investigate how these parameters influence children’s TMC. The results suggest that MOHPT outperforms conventional methods in tuning hyperparameters on the basis of prediction accuracy and computational cost. Trip distance, “walkability” and “bikeability” of the origin location, age, and household income are principal determinants of child mode choice. Furthermore, older children, those who live in walkable and bikeable areas, those belonging low-income groups, and short-distance travelers are more likely to travel by sustainable transportation modes.

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Modelling effects of changes in travel time and costs of toll road usage on choices for residential location, route and travel mode across population segments in the Jakarta-Bandung region, Indonesia

Cited by 14 publications

References 53 publications

Exploring the Effects of Carpooling on Travelers’ Behavior during the COVID-19 Pandemic: A Case Study of Metropolitan City

Exploring the Effects of Carpooling on Travelers’ Behavior during the COVID-19 Pandemic: A Case Study of Metropolitan City

Factors Affecting Customer Loyalty: An Empirical Evidence from the Toll Road Industry in Indonesia

Application of Machine Learning to Child Mode Choice with a Novel Technique to Optimize Hyperparameters

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