Phd Dissertation

Low-Wage Workers & Commuting: The Social, Spatial, and Temporal Patterns of Employment in Los Angeles

Publication Date

January 1, 2024

Author(s)

Abstract

Commute patterns can reflect multiple dimensions of urban inequality, primarily access to housing, jobs, and transportation. Researchers have sought to understand and predict commute behavior to identify and address such inequities, especially among disadvantaged workers and communities. In this dissertation, I analyzed the relationship between commute duration and the social, spatial, and temporal patterns of low-wage jobs. In particular, I examined the heterogeneity of low-wage jobs, in terms of whether they offer full-employment or employer-sponsored health insurance, as well as their spatial and temporal distribution; whether and how it relates to commute durations; and compared these aspects with high-wage workers. This research advances what we know about low-wage workers and commuting by centering the analysis on low-wage jobs – as opposed to workers. I used the Integrated Public Use Microdata Sample (IPUMS) American Community Survey (ACS) 1- year data for 2019, before the onset of the COVID-19 pandemic in March 2020. I focused my analyses on the five-county Los Angeles Metropolitan Area – Los Angeles, Orange, Ventura, Riverside, and San Bernardino. I applied ordinary least squares regression models in the first and third chapters, and multi-level models in the second chapter to predict commute times among low-wage workers, and compared them to high-wage workers. I found that employment characteristics are significant predictors of commute patterns among low-wage workers. Improving job quality could reduce the commute burden of many low-wage workers – instead of engaging in long commutes to jobs that offer wage and employment security, low-wage workers could engage in short commutes to more spatially accessible, consumer-oriented service sector jobs. The second empirical chapter contributes to the literature on low-wage workers and commuting by estimating the effects of the industry of employment, since labor and employment policies more often address industries, e.g., sector-based minimum wage increases, and industry-level regulations have more coverage. Finally, low-wage workers who commute during rush hour have longer commute times than low-wage workers who commute during off-peak hours, while high-wage workers have the opposite relationship, which suggests that high-wage workers have greater residential mobility and location selection, while low-wage workers experience spatial mismatch. The results of these studies suggest that more equitable transportation planning can be informed by labor markets, or how better labor and employment policies can inform transportation planning.

Suggested Citation
Youjin B. Kim (2024) Low-Wage Workers & Commuting: The Social, Spatial, and Temporal Patterns of Employment in Los Angeles. PhD Dissertation. UC Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/u4evf/cdi_proquest_journals_3117801959.

published journal article

Potential for a logistics island to circumvent container port congestion in a constrained environment

Transport Policy

Publication Date

February 1, 2020

Author(s)

Michael Hyland, Lama Bou-Mjahed, Hani Mahmassani, I. Omer Verbas, Xiang (Alex) Xu, Karen Smilowitz, Breton Johnson
Suggested Citation
Michael Hyland, Lama Bou-Mjahed, Hani S. Mahmassani, I. Omer Verbas, Xiang (Alex) Xu, Karen Smilowitz and Breton Johnson (2020) “Potential for a logistics island to circumvent container port congestion in a constrained environment”, Transport Policy, 86, pp. 50–59. Available at: 10.1016/j.tranpol.2019.06.011.

published journal article

Channel state information-based cryptographic key generation for intelligent transportation systems

IEEE Trans. Intell. Transport. Syst.

Publication Date

January 1, 2020

Author(s)

Soheyb Ribouh, Kelvin Phan, Arnav Vaibhav Malawade, Yassin Elhillali, Atika Rivenq, Mohammad Al Faruque
Suggested Citation
Soheyb Ribouh, Kelvin Phan, Arnav Vaibhav Malawade, Yassin Elhillali, Atika Rivenq and Mohammad Abdullah Al Faruque (2020) “Channel state information-based cryptographic key generation for intelligent transportation systems”, IEEE Trans. Intell. Transport. Syst., pp. 1–12. Available at: 10.1109/tits.2020.3003577.

conference paper

Investigation of the operational characteristics of vocational natural gas vehicles in southern California and their influence on nitrogen oxide emission productions by road type

Proceedings of the 98th annual meeting of the transportation research board

Publication Date

January 1, 2019

Abstract

Understanding the operational characteristics of vocational trucks, and developing a method to assess the suitability of the vocation types with various fuel types is a cornerstone (backbone) of successful fuel transition from incumbents to clean alternatives. With the collected in-vehicle controller area network (CAN) data, operational characteristics of the three vocational CNG vehicle types are analyzed and compared with each other. Through pattern clustering and classification process, the obtained vehicle activity data is translated into drive mode compositions (DMC) which are associated with driving situations and operation conditions. Drive mode composition indicates how a vehicle is being operated in terms of time and distance. To assess the vehicle operation in a stereoscopic view, the obtained vehicle trajectories are geo-mapped into the open-street map and segmented by road facility type which is defined by highway functional classes. The analysis results present that each drive mode has different nitrogen oxides (NOâ??) emission factors in grams per mile or second. Another finding is that vocation type is one of the influential factor determining vehicle activity and environmental impact potential. In addition, it is found that drive mode composition changes over different road facility types and by road conditions, such as trip distance and duration. DMC for each facility trip shows a clearer picture of the operational characteristics between the considered vocation types. The proposed anatomical analysis on vehicle activity can be used to resolve a variety of research issues and policies related with alternative fuel and clean energy vehicles.

Suggested Citation
Junhyeong Park, Craig Rindt, Andre Tok and Stephen G. Ritchie (2019) “Investigation of the operational characteristics of vocational natural gas vehicles in southern California and their influence on nitrogen oxide emission productions by road type”, in Proceedings of the 98th annual meeting of the transportation research board, p. 8p.

book/book chapter

Regional and Urban Economics

Publication Date

January 1, 1997

Author(s)

Suggested Citation
Kenneth A. Small (1997) Regional and Urban Economics. 1st ed. Routledge.

published journal article

A surrogate-based multiobjective metaheuristic and network degradation simulation model for robust toll pricing

Optimization and Engineering

Publication Date

August 1, 2013
Suggested Citation
Joseph Y.J. Chow and Amelia C. Regan (2013) “A surrogate-based multiobjective metaheuristic and network degradation simulation model for robust toll pricing”, Optimization and Engineering, 15(1), pp. 137–165. Available at: 10.1007/s11081-013-9227-5.

conference paper

Intelligent and collaborative embedded computing in automation engineering

2012 design, automation & test in europe conference & exhibition (DATE)

Publication Date

March 1, 2012

Author(s)

Mohammad Al Faruque, A. Canedo
Suggested Citation
M.A. Al Faruque and A. Canedo (2012) “Intelligent and collaborative embedded computing in automation engineering”, in 2012 design, automation & test in europe conference & exhibition (DATE). IEEE, pp. 344–345. Available at: 10.1109/date.2012.6176494.

working paper

Truck-Involved Crashes and Traffic Levels on Urban Freeways

Abstract

Using two years of crash and average annual daily traffic data we examine the locations and conditions linked to truck-involved crashes (accidents). A binomial logit model is used to describe how the probability that a crash involves a truck is a function of the percentage of annual average daily traffic that is accounted for by trucks, time of day, day of the week, weather conditions, mix of truck types, and the absolute level of average annual daily traffic. That model can then be used to identify locations with higher or lower than expected truck involved accident rates, controlling for all of the factors that influence truck crash rates. A multinomial logit model was then estimated in order to better understand patterns of truck-involved crashes by separating crashes by type, with the main types being rear-end, lane-change, and run-off collisions. We propose that results from applications of these kinds of models, applied in a specific region, can be useful to public agencies seeking to identify and remedy problem areas either with better driver education or investments in physical or intelligent transportation system infrastructure.

conference paper

A GPS Enhanced In-Vehicle Extensible Data Collection Unit

Proceedings of the 80th Annual Meeting of the Transportation Research Board

Publication Date

January 1, 2001

Author(s)

Abstract

The rapid advancement of technology has created the opportunity for applying new, powerful tools to transportation engineering problems but often the very speed of technological change hinders the adoption of these tools in a research environment. This paper documents the development of an extensible data collection unit (EDCU). The unit combines a standard GPS unit, a cellular data modem, and an embedded processor running the Linux operating system. The EDCU satisfies multiple functional requirements, due to the flexibility of its modular components and its full-powered operating system. The EDCU will serve the in-vehicle data collection needs of travel demand modelers and ITS researchers for the foreseeable future

Suggested Citation
James E. Marca, Craig R. Rindt, Michael G. McNally and Sean Doherty (2001) “A GPS Enhanced In-Vehicle Extensible Data Collection Unit”, in Proceedings of the 80th Annual Meeting of the Transportation Research Board, p. 21 p..

conference paper

Long-haul freight network design using shipper-carrier freight flow prediction: California network improvement case study

Proceedings of the 88th annual meeting of the transportation research board

Publication Date

January 1, 2009

Abstract

Transportation network design is a method for analyzing the interactive benefits of transportation projects applied to a network. In this paper, a network design model is developed for long haul freight movements which are represented by relationships between shippers and carriers. Additionally, an explicit capacity constraint is used to divert traffic volume from congested links. A case study based on the California transportation network is implemented to examine the effectiveness of this model when applied to a large network. A geographic information system is used to facilitate data management and analysis of the results.

Suggested Citation
Pruttipong Apivatanagul and Amelia Regan (2009) “Long-haul freight network design using shipper-carrier freight flow prediction: California network improvement case study”, in Proceedings of the 88th annual meeting of the transportation research board, p. 41p.