How disruptive is a disruption? The association between TNCs and vehicle ownership in urbanizing Indonesia

Widita, Alyas; Diwangkari, Andyan

doi:10.1016/j.cstp.2022.01.017

Cited by 5 publications

(5 citation statements)

References 26 publications

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“…While this overall trend is expected (and supports empirical findings e.g. from [ 52 ] and [ 53 ]), the magnitude and the sensitivity of these relations and their potential to result in feedback loops on both the demand and supply sides of the two-sided market would not have been possible without detailed modelling with .…”

Section: Resultssupporting

confidence: 82%

Simulating two-sided mobility platforms with MaaSSim

Kucharski

Cats

2022

PLoS ONE

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Two-sided mobility platforms, such as Uber and Lyft, widely emerged in the urban mobility landscape. Distributed supply of individual drivers, matched with travellers via intermediate platform yields a new class of phenomena not present in urban mobility before. Such disruptive changes to transportation systems call for a simulation framework where researchers from various and across disciplines may introduce models aimed at representing the complex dynamics of platform-driven urban mobility. In this work, we present MaaSSim, a lightweight agent-based simulator reproducing the transport system used by two kinds of agents: (i) travellers, requesting to travel from their origin to destination at a given time, and (ii) drivers supplying their travel needs by offering them rides. An intermediate agent, the platform, matches demand with supply. Agents are individual decision-makers. Specifically, travellers may decide which mode they use or reject an incoming offer; drivers may opt-out from the system or reject incoming requests. All of the above behaviours are modelled through user-defined modules, allowing to represent agents’ taste variations (heterogeneity), their previous experiences (learning) and available information (system control). MaaSSim is a flexible open-source python library capable of realistically reproducing complex interactions between agents of a two-sided mobility platform. MaaSSim is available from a public repository, along with a set of tutorials and reproducible use-case scenarios, as demonstrated with a series of illustrative examples and a comprehensive case study.

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Section: Resultssupporting

confidence: 82%

Simulating two-sided mobility platforms with MaaSSim

Kucharski

Cats

2022

PLoS ONE

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“…They also estimate a larger effect in eastern than in western cities. Similarly [53], find that the entry of Gojek and Grab, two ride-hailing companies, into Indonesian cities resulted in a 1.1% decline in per capita vehicle ownership. Wadud and Namala [54] find that Ola and Uber have jointly reduced vehicle ownership in various Indian cities by 7.7% since their introduction.…”

Section: Vehicle Ownershipmentioning

confidence: 99%

“…Six papers using a DiD strategy to investigate the impact of TNC entry on vehicle ownership [14, [51][52][53][54][55]. Ride-hailing could decrease vehicle ownership if drivers substituted away from private vehicles.…”

Section: Vehicle Ownershipmentioning

confidence: 99%

Impacts of ride-hailing on energy and the environment: a systematic review

Sheldon,

Dua

2024

Environ. Res. Lett.

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Ride-hailing has expanded substantially around the globe over the last decade and is likely to be an integral part of future transportation systems. We perform a systematic review of the literature on energy and environmental impacts of ride-hailing. In general, empirical papers find that ride-hailing has increased congestion, vehicle miles traveled, and emissions. However, theoretical papers overwhelmingly point to the potential for energy and emissions reductions in a future with increased electrification and pooling. Future research addressing the gap between observed and predicted impacts is warranted.

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“…Orientasi tersebut sejalan dengan prinsip dan dimensi pembangunan berkelanjutan, di mana terdapat kesetaraan antargenerasi, keadilan sosial, dan tanggung jawab dalam pengelolaan lingkungan yang efektif (Haughton dan Hunter, 1994 dalam Kustiwan & Ramadhan (2019), serta memiliki fungsi penjagaan lingkungan, fungsi ekonomi, dan sosial (Kustiwan & Ramadhan, 2019) serta kelembagaan (Setianingtias dkk., 2019). Maka beragam masalah muncul, seperti kemiskinan, krisis pangan (Suryandari, 2010), kepadatan penduduk, persaingan kerja semakin tinggi, pengangguran, kriminalitas, permukiman kumuh, kemacetan, degradasi lingkungan, dan lain sebagainya (Indraprahasta & Agustina, 2012;Handayani dkk., 2018;Hidayati, 2021;Widita & Diwangkari, 2022).…”

Section: Pembangunanunclassified

Urban Farming sebagai Alternatif Mewujudkan Pembangunan Kota Berkelanjutan di Indonesia

Armansyah,

Giyarsih,

Fathurohman

et al. 2024

kawistara

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Tingkat urbanisasi di Indonesia semakin tinggi, sedangkan luasan lahan produktif pertanian semakin berkurang. Padahal penduduk perkotaan memerlukan lahan untuk permukiman, bertanam, untuk ruang terbuka hijau, ruang berinteraksi dan bersosialisasi, rekreasi, dan sebagainya. Munculnya urban farming menjadi salah satu alternatif dalam menjawab permasalahan akibat urbanisasi. Penelitian ini bertujuan mengeksplorasi keterkaitani urban farming dan urbanisasi dalam upaya mewujudkan pembangunan kota berkelanjutan. Penelitian ini merupakan bagian awal dari upaya membuat model integrasi urban farming for urbanization untuk ketahanan pangan penduduk perkotaan (2023-2025) pada skema Riset Inovasi untuk Indonesia Maju (RIIM). Penelitian ini memakai metode kualitatif dengan informan sebagai sampel sumber datanya. Informan dipilih menggunakan teknik purposive sampling, yang berjumlah 30 pelaku urban farming, dengan rincian 10 informan dari Kota Palembang, 10 dari Kota Bandung, dan 10 dari Kota Denpasar. Pengumpulan melalui tahapan observasi, wawancara mendalam, dan dokumentasi. Analisis data menggunakan Model Miles dan Hubberman dengan tiga tahapan, yaitu reduksi data, display data, dan penarikan kesimpulan. Teknik uji keabsahan data menggunakan trianggulasi dengan metode cross check. Hasil analisis menemukan keterkaitan urban farming dan urbanisasi pada sembilan dimensi, yaitu; ekonomi, sosial, lingkungan, kesehatan, budaya, pangan, edukasi, wisata, dan teknologi. Katerkaitan urban farming dan urbanisasi bersifat positif, yang bermakna dampak positif urban farming memiliki indikasi meminimalisir dampak negatif urbanisasi. Selain itu, keterkaitan tersebut juga relevan dengan tiga prinsip pembangunan berkelanjutan, yaitu memiliki fungsi mengontrol dampak lingkungan seminimal munkin, fungsi ekonomi, dan sosial.

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How disruptive is a disruption? The association between TNCs and vehicle ownership in urbanizing Indonesia

Cited by 5 publications

References 26 publications

Simulating two-sided mobility platforms with MaaSSim

Simulating two-sided mobility platforms with MaaSSim

Impacts of ride-hailing on energy and the environment: a systematic review

Urban Farming sebagai Alternatif Mewujudkan Pembangunan Kota Berkelanjutan di Indonesia

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