Modelling Sustainable Urban Transport Performance in the Jakarta city Region: A GIS Approach

Nadi, Puji Adiatna; Murad, Abdulkader A.

doi:10.3390/su11071879

Cited by 15 publications

(13 citation statements)

References 51 publications

(59 reference statements)

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“…is is because access to using e-hailing is very easy with tariffs determined based on distance and traffic conditions [76]. e ease of using e-hailing services is supported by the provision of transport infrastructure in Jakarta, which currently leads to sustainable transport [48]. Furthermore, accessibility and connectivity between modes and the development of information technology that supports travel have allowed the use of e-hailing to become an alternative capable of competing with other modes of commuting.…”

Section: Discussionmentioning

confidence: 99%

“…Considering that in urban areas, sustainable transport needs to be encouraged [48,49], this study considers trip characteristics, transport infrastructure and services, environment, and work characteristics as stimulus factors that influence the response to transport modes through travel experience and attitude factors as organisms. In this study, response is a variable that describes the public transport, private transport, and e-hailing usages.…”

Section: Hypothesis Developmentmentioning

confidence: 99%

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How Employees Choose their Commuting Transport Mode: Analysis Using the Stimulus-Organism-Response Model

Djakfar

Bria

Wicaksono

2021

Journal of Advanced Transportation

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Although transport mode choice in commuting from home to work has been studied extensively, no prior research has investigated mode choice as an emotional response to external stimuli using the stimulus-organism-response (SOR) model. Therefore, this study applies the SOR model to explore commuters’ transport mode choice behaviour. The stimulus variables include trip characteristics, transport infrastructure and services, environment, and work characteristics; the organism variable includes the travel experience and attitude of the individual; and the response variables include use of public transport, private transport, and e-hailing. Data were collected using a questionnaire survey of 500 formal-sector workers in Jakarta; 430 respondents provided valid responses for analysis. The survey data were analysed using partial least squares-structural equation modelling. The results showed that the stimulus variables, namely, trip characteristics, transport infrastructure, environment, and work characteristics, had indirect effects on the choice of e-hailing through organism factors (travel experience and attitude). Also, the environment and work characteristic variables had an indirect effect on the choice of private transport through organism factors. Stimulus variables had no indirect effects on public transport usage. When travel experience was the stimulus variable, the indirect effect on public transport usage through attitude as the organism variable was significant. The response to the use of transport modes showed dynamic behaviour, depending on the provided stimulus and organism. These findings can be beneficial for establishing a more comprehensive strategy that includes the provision of infrastructure, improvement of transit service, the built environment, and employers’ policies to realise a sustainable commuting trip.

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Section: Discussionmentioning

confidence: 99%

Section: Hypothesis Developmentmentioning

confidence: 99%

How Employees Choose their Commuting Transport Mode: Analysis Using the Stimulus-Organism-Response Model

Djakfar

Bria

Wicaksono

2021

Journal of Advanced Transportation

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“…The kernel density estimation method solves the distribution density of the residential space according to the point dataset of the residential district [51][52][53]. The spatial distribution characteristics of the data were studied starting from the kernel density estimation sample itself.…”

Section: Kernel Density Estimation Methodsmentioning

confidence: 99%

The Evolution of the Urban Residential Space Structure and Driving Forces in the Megacity—A Case Study of Shenyang City

Sun

Guan

et al. 2021

Land

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For megacities, they are in a period of transformation from extensive development to smart growth. Recognizing new characteristics and new changes of the residential space in megacities under the backdrop of new development has great practical significance for realizing the sustainable development of the city. As the only megacity in Northeast China, Shenyang was selected to be the research object, with 1989–2018 as the research period. The research comprehensively used multiple spatial representation methods and statistical methods to study the residential space pattern and driving factors in Shenyang City. The results showed that: (1) Residential space expansion can be divided into four stages: slow development, rapid expansion, speedy expansion, and stable extension. (2) The residential space structure presented a spatial evolution characteristic of overall expansion, forming multiple secondary core density centers. The east-west direction had a larger extension range than the northeast-southwest direction. There was an axisymmetric zonal distribution on both sides of the Hun River. (3) The agglomeration of different residential forms was obvious, and the spatial heterogeneity was increasingly stronger. (4) Urban planning measures and economic strength were the main driving forces of residential space expansion.

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“…This aggregation method is used when full compensation between elementary indicators is deemed unacceptable. Thus, an unfavorable result of one indicator cannot be compensated by a favorable result provided by another indicator Researchers, in [9][10][11], applied cartographic composite indicators relying on a spatial analysis of a geographic information system. More precisely, Yigitcanlar and Dur suggested, in [11], a composite indicator to compare and assess urban sustainability and, then, to aid decision makers in forming sustainable transport development policies.…”

Section: De Nition Of Composite Indicatorsmentioning

confidence: 99%

Assessing sustainability of transport system through index: A state-of-the-art review

Ayadi

Benaissa

Hamani

et al. 2022

Preprint

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The transport is one of the most important sectors that affect the economic development. However, its sustainability may be disturbed due to the remarkable increase in the number of vehicles in city centers and its bad consequences, hence the importance of assessing the transport system and the performance of its different components. Therefore, several evaluation methods were introduced to help decision-makers assess sustainability and many indicators were developed to track the progress of sustainable transport system. This work provides a literature review about the existing approaches used to assess transport sustainability through composite indicators. It aims at analyzing the trends in the existing literature, identifying gaps in evaluating sustainability and suggesting future research perspectives. A total of 47 studies conducted in the period 2002–2022 are examined. The obtained results show that few researchers focused on freight transportand most researchers considered only traditional sustainability dimensions. In addition, the performed analysis demonstrates that the use of different methods of normalization, weighting and aggregation influences the result given by composite indicator. Finally, a set of recommendations for precise and correct sustainability assessment is presented in order to develop future research.

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Modelling Sustainable Urban Transport Performance in the Jakarta city Region: A GIS Approach

Cited by 15 publications

References 51 publications

How Employees Choose their Commuting Transport Mode: Analysis Using the Stimulus-Organism-Response Model

How Employees Choose their Commuting Transport Mode: Analysis Using the Stimulus-Organism-Response Model

The Evolution of the Urban Residential Space Structure and Driving Forces in the Megacity—A Case Study of Shenyang City

Assessing sustainability of transport system through index: A state-of-the-art review

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