An Empirical Study on the Relationship between Urban Railway Ridership and Socio-economic Characteristics

Lee, Kwang Sub; Eom, Jin Ki; You, So Young; Min, Jae Hong; Yang, Keun Yul

doi:10.1016/j.procs.2015.05.037

Cited by 8 publications

(9 citation statements)

References 1 publication

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“…Previous research was used to determine what other data should be collected and included in the model (5)(6)(7)(8)(9). Table 1 shows an overview of significant influencers of transit ridership with previous models.…”

Section: Datamentioning

confidence: 99%

“…Whereas the goal of the previous papers was to forecast transit ridership, the following papers explore the effects of various factors on transit ridership. Lee et al ( 6 ) study the relationships between heavy and light rail ridership and socioeconomic characteristics in South Korea. They find that heavy rail ridership is correlated with the density of businesses and households, whereas light rail ridership is correlated with the density of economically active population and businesses.…”

mentioning

confidence: 99%

“…Whereas DRMs are routinely promoted as tools for forecasting ( 2 , 4 ), they are rarely evaluated for their ability to forecast. In fact, many of the published DRMs evaluate the models exclusively on the goodness of fit against the estimation data set, without any validation against independent data in either location or time ( 2 – 9 ). An exception to this is Upchurch and Kuby ( 12 ) in which a DRM is estimated using data in nine (other) cities, applied to predict the ridership on a new light rail line in Phoenix, and compared to actual ridership.…”

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confidence: 99%

See 2 more Smart Citations

Evaluating the Ability of Transit Direct Ridership Models to Forecast Medium-Term Ridership Changes: Evidence from San Francisco

Mucci

Erhardt

2018

Transportation Research Record: Journal of the Transportation R

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Transit direct ridership models (DRMs) are commonly used both for descriptive analysis and for forecasting, but are rarely evaluated for their ability to predict beyond the estimation data set. This research does so, using two DRMs estimated for rail and bus ridership in San Francisco. The models are estimated from 2009 data, applied to predict 2016 conditions, and compared to actual 2016 ridership. Over this period in San Francisco, observed rail ridership increased by 9% whereas observed bus ridership decreased by 13%. The results show that the models predict 2016 ridership about as well as that for 2009. The rail model correctly predicts the direction of change, but underestimates the magnitude of change. The bus model predicts the direction of change incorrectly, with a predicted 2% increase. A series of sensitivity tests are conducted to better understand the factors driving the ridership changes. These tests produce reasonable rail sensitivities, but reveal that the bus model is too sensitive to frequency, potentially because of the difficulty of estimating the coefficient from cross-sectional data when high-frequency transit also occurs in high-density locations. As the travel forecasting community increases its focus on empirically evaluating forecasts beyond a base year, DRMs must be a part of that.

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Section: Datamentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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Evaluating the Ability of Transit Direct Ridership Models to Forecast Medium-Term Ridership Changes: Evidence from San Francisco

Mucci

Erhardt

2018

Transportation Research Record: Journal of the Transportation R

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“…Penggunaan LRT dan MRT identic dengan pusat bisnis dan wilayah dengan populasi tinggi dan secara ekonomi aktif (K. S. Lee, Eom, You, Min, & Yang, 2015). Selain itu, faktor penting lainnya yang ikut mendorong seseorang menggunakan layanan kereta api adalah infrastruktur layanan tersebut dan karakteristik layanannya seperti ketersediaan bus penghubung, layout rute dan sebagainya (Chen & Zegras, 2016 Sumber: UIC (2014) ridership LRT (Currie & Delbosc, 2013).…”

Section: Pendahuluanunclassified

Clastering Calon Penumpang Kereta Cepat Jakarta-Bandung

Firdaus

Octaviani

Yusnita

2017

j. manaj. transp. logist.

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ABSTRAKPenelitian ini bertujuan untuk membuat klaster (pengelompokan) calon penumpang layanan kereta cepat (high speed railway) koridor Jakarta-Bandung untuk mengimbangi semakin pesatnya perkembangan kota Bandung sebagai salah satu destinasi pariwisata favorit baik bagi pengunjung domestik maupun internasional. Penelitian ini menggunakan metode kuantitatif dan analisis data menggunakan non-hierarchical cluster analysis serta penentuan sampling secara random sampling dengan 280 responden. Hasil penelitian menunjukkan terdapat tiga klaster calon penumpang layanan kereta cepat ini dengan karakteristik yang berbeda. Klaster pertama sangat bergantung pada kendaraan pribadi, klaster kedua merupakan klaster terbesar memiliki karakteristik ridership yang logis dan klaster terakhir adalah kelompok yang memiliki tingkat kepedulian terhadap lingkungan yang tinggi.

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“…Several studies conducted have found that socio-demographic variables play a significant role in the demand for transportation (Cheng & Chen, 2015;Lee, Eom, You, Min, & Yang, 2015;Terayama & Odani, 2017). The indicators include gender, age (children, teenager, adult, and older), level of education, occupation or current status whether the person is employed or unemployed, and income (Clark, Chatterjee, & Melia, 2016;Şimşekoğlu, Nordfjaern, & Rundmo, 2015;Sundling et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Understanding People’s Acceptance of Light Rail Transit in Bandung and Its Determinant Factors

Shadrina

Lestari

2019

Binus Business Review

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The aim of this research was to verify the readiness of Bandung people in accepting Light Rail Transit (LRT) as the new transport option. Through a survey questionnaire with various respondent backgrounds, the researchers applied statistical analysis using ANOVA to compare the acceptance between the group of gender, age, occupation, income, home location, mobility pattern, and current transport. As the extension, the research also explored the factor determining people’s priority in choosing transport and showing attributes (comfort, security and safety, exclusivity, time travel, cost, flexibility, facility, and accessibility). The result reveals that there are no differences between-group comparisons in accepting LRT as the new transport. In analyzing the determinant factors, the result shows that passengers tend to value security and comfort for their daily activities in choosing public transportation. Meanwhile, the exclusivity and facility are considered undesirable for passengers in deciding to take public transportation for travel. LRT is considered as a mode transport that provides sustainable transportation value. The readiness of passenger and market environment to the sustainable transportation option is important to maintain the successful implementation of the LRT project in Bandung.

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An Empirical Study on the Relationship between Urban Railway Ridership and Socio-economic Characteristics

Cited by 8 publications

References 1 publication

Evaluating the Ability of Transit Direct Ridership Models to Forecast Medium-Term Ridership Changes: Evidence from San Francisco

Evaluating the Ability of Transit Direct Ridership Models to Forecast Medium-Term Ridership Changes: Evidence from San Francisco

Clastering Calon Penumpang Kereta Cepat Jakarta-Bandung

Understanding People’s Acceptance of Light Rail Transit in Bandung and Its Determinant Factors

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