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原文传递 Economic Analysis of Public Transportation in Reno, Nevada

题名：	Economic Analysis of Public Transportation in Reno, Nevada
作者：	Song, S.
关键词：	Economic analysis##Public transportation##Reno (Nevada)##Workers##High density levels##Low-income workers##
摘要：	Access to public transit is important and beneficial economically and socially in numerous ways. Using economic and demographic variables from U.S. Census data, we have examined who is being served by public transit in Reno, as well as examined the flow of workers to their jobs to identify possible locations for expansion. We focus on areas with high densities of workers and jobs, especially those that are low income. The first part of our research looks at access to public transit, which we define as individuals living or working within 400 meters of a bus stop. The second part of the research consists of an analysis on use of public transit. We have been conducting regression analyses on the factors that influence choice of transportation to work. After our data analyses, we have found locations that are possibly being underserved by public transit based on our specified criteria. The focus was placed on areas of high density levels of workers and jobs, with an emphasis on low-income workers. From our analysis on public transit access, we have found that there are several areas that have strong potential for usage should the RTC expand its service to those areas. There are four important findings from this research: (1) There are several areas that have strong potential for usage if the RTC were to expand its service to those areas. (2) Many non-served areas we identified had higher densities of individuals likely to take public transit than areas currently being served. (3) The regression analyses support the idea of lower income individuals being more likely to take public transit. (4) The regressions also show that race is an important factor in addition to income. Many of the non-served areas we identified had higher densities of individuals likely to take public transit than some of the areas currently being served. Our regression analyses support the idea of lower income individuals being more likely to take public transit. Additionally, the regressions show us that not only is income an important factor, but race is influential as well. These results can be helpful in terms of locating good quality locations for public transit service, as well as identifying the current service locations that may not be as good. This research has shown that there are numerous areas with strong potential for public transit usage, as well as areas that are possibly being overserved.
总页数：	36
报告类型：	科技报告