Brandon Figliolino
PUAD 5361 Capstone Prospectus
Assessing Employer Transportation Needs in the Denver Metropolitan Area
CLIENT OVERVIEW:
The Denver Regional Council of Governments (DRCOG) is a non-profit organization made up of municipalities, counties, and other governing bodies located within the Denver Metropolitan Area. DRCOG focuses on regional planning, including planning for transportation and mobility. They aim to make commuting across the region easier by increasing the use of public transportation, biking, walking, and ridesharing services. To meet this goal, the organization distributes funding and provides guidance to governments and transportation management associations (TMAs) through their Way to Go program.
BACKGROUND INFORMATION:
The Denver Metropolitan Area is experiencing a surge in new residents. As of July 1, 2018, the area reached a population of 2.9 million people (Murray, 2018). This population increase is putting constraints on current transportation infrastructure by increasing the amount and severity of traffic congestion.
Instead of combating congestion through road and highway expansion projects, more governments—including those within Colorado—are working on reducing single occupancy vehicle (SOV) use by encouraging public transportation, ridesharing, and biking as alternatives (Henao, Luckey, Nordback, Marshall, & Krizek, 2012; Tanadtang, Park, & Hanaoka, 2005; Yao, Yan, Chen, Tian, & Zhu, 2018). To help facilitate this change, Transportation Management Associations (TMAs) work with governments and employers to make it easier, more efficient, and safe to use these alternative modes of transportation. The services and programs they offer are referred to commonly as transportation demand management (Ferguson, 1990).
PROJECT PURPOSE & SCOPE:
This research project aims to help the Denver Regional Council of Governments (DRCOG) and their TMA partners identify areas where they can expand transportation demand services (TDM). This will be performed through a mixed-methods study that surveys both employers and transportation management association personnel to identify current program participation and future needs. Information collected will be analyzed and used to identify program areas that DRCOG and the TMA partners can expand to further reduce the regional use of single occupancy vehicles. The study will seek to answer the following questions, and determine the accuracy of the following hypotheses:
RQ1: What TDM services do employers currently offer their employees? H1: Most employers will participate in the RTD EcoPass and DRCOG Guaranteed Ride Home programs.
RQ2: Which TDM services would employers like to offer their employees in the future?
H2: Employers will want to expand carpool and vanpool opportunities, as those services do not rely as much on transit infrastructure to be successful.
RQ3: What barriers are inhibiting employers from expanding current TDM services?
H3.1: Employee demand for services, as well as the cost of implementing them, will be the biggest challenges to program expansion.
H3.2: Some employers will not believe they have a responsibility to offer such services.
RQ4: What resources can TMAs offer employers to help reduce barriers to expanding services?
H4: TMAs can offer ongoing administrative support to help encourage employer participation, which reduces the need for employers to have dedicated TDM staff.
RQ5: What are the subarea differences in TMA services and desired programs in the Denver Metropolitan Area?
H5: TMAs in suburban-centered areas will offer fewer services and more carpool and vanpool options than those in dense corridors.
PROJECT RATIONALE:
This proposed study offers several benefits to DRCOG. First, it aligns directly with the Way to Go program goal of reducing SOV use. This is done through studying work commuting behaviors. By identifying current commuting patterns, DRCOG can determine which TDM programs could expand to further reduce SOV use.
Second, the study provides an updated snapshot of work commuting. The most recent employer-focused TDM survey for the region was conducted in 2015, and looked at the extent to which employers had adopted TDM programs, and which programs had the potential for expansion. Results from this study can be compared with the 2015 study to determine if progress has been made in increasing the use of specific SOV alternatives.
This study also expands upon the 2015 study in two ways. First, it incorporates the insights of TMAs, which will allow DRCOG and partners the ability to identify areas where TMAs and employers are not in alignment. This gap analysis will help improve communication between TMAs and employers, and help TMAs better serve employers. Second, the study identifies subarea differences and similarities in TDM programming, which can be used to better improve alternative transportation use regionally.
METHODOLOGY:
The transportation needs study will utilize a mixed-methods approach. Components include an online survey, to be distributed to employers throughout the region. The list of employers will be gathered from a variety of sources, including TMA partners, chambers of commerce, and other DRCOG partners. In addition to the online survey, a qualitative interview with TMA partner coordinators will be conducted. The data will be compiled into multiple analyses to determine if employer needs are being met, how barriers to participation can be reduced, and if there are differences in needs between subareas.
LITERATURE REVIEW:
A preliminary review of literature was conducted. Based on the review of past studies, there is no commonly accepted way to study the effectiveness of transportation demand management programs (Finke & Schreffler, 2004; Hasnine, Weiss, & Habib, 2017; Wallace, Mannering, & Rutherford, 1999; Yao, Yan, Chen, Tian, & Zhu, 2018). Regardless of the different measures utilized, most results show that TDMs based on specific sites are more effective than regionally-based ones (Collura, 1994; Hasnine, Weiss, & Habib, 2017).
Past studies fall into two categories: a priori and ex post. A priori studies of TDM effectiveness measure awareness of TDM programs, while ex post measures use of alternative modes of transportation, including air pollution reduction and vehicle miles traveled (Finke & Schreffler, 2004). There are issues with both these types of studies. A priori studies might not reflect the accurate level of participation in TDM programs; just because a survey-taker is aware of a program does not necessarily mean they are using it (Finke & Schreffler, Hasnine, Weiss, & Habib, 2017). Ex post studies are also challenging because of the difficulty associated with quantifying outcomes, including air pollution reduction from using a non-SOV form of transportation (Hasnine, Weiss, & Habib, 2017).
Regardless of the lack of commonly used survey methodologies, over the past three decades there have been some effective studies that can be used as a basis for this research project. Most relevant is a study conducted in 2015 by DRCOG that measured the potential TDM programs in the Denver Metropolitan Area had to expand. Employers who participated in RTD’s EcoPass program, members of the Mile High Society of Human Resources Management, and members of DRCOG’s Way to Go were surveyed online. Results showed that participation rates in TDM programs ranged from 1 to 10% (“Denver Regional Employer Survey,” 2015). This study will be a critical link to this transportation needs study, as it will help DRCOG evaluate TDM programs over time.
Another pertinent piece of literature for this study is the study conducted by Finke & Schreffer (2004). They reviewed multiple TDM assessment tools across the country, including in Georgia and California, and determined that the most effective means of evaluating TDM program success is by having multiple measures of testing.
Other literature has also been reviewed that expand upon the basic principles of TDM evaluation. They will be incorporated into a final literature review. Because much of the literature that has been reviewed for this study was published in the 1990s, additional searches for more current data is warranted.
REFERENCES:
Collura, J. (1994) “Evaluating ride sharing programs: Massachusetts’ experience.” Journal of Urban Planning and Development. 120:1.
“Denver Regional Employer Survey.” (2015) Way to Go.
Ferguson, E. (1990) “Transportation demand management planning, development, & implementation.” Journal of American Planning Association. 56:4
Finke, T. & Schreffler, E. (2004) “Using Multiple Assessment Levels for Evaluating Transportation Demand Management Projects: Monitoring and Evaluation Toolkit.” Journal of the Transportation Research Board. Vol. 1864.
Hasnine, S., Weiss, A. & Habib, K. (2017) “State preference survey pivoted on revealed preference survey for evaluating employer-based travel demand management strategies.” The Journal of the Transportation Research Board. 2651.
Henao, A., Piatowsi, D., Luckey, K., Nordback, K, Marshall, W., & Krizek, K. (2012) “Sustainable transportation infrastructure investments and mode sharing changes: A 20 year background of Boulder, Colorado.” Transport Policy. 37: pp. 64-71.
Murray, J. (2018) “Denver grew by 100,000 people in just 7 years—but the pace has slowed for the 2nd straight year.” The Denver Post. Retrieved from: https://www.denverpost.com/2018/03/22/denver-population-growth-100000-7-years-pace-slowing/.
Tanadtang, P., Park, D., & Hanaoka, S. (2005) “Incorporating uncertain and incomplete subjective judgments into the evaluation procedure of transportation demand management.” Transportation. 32:6.
Wallace, B., Mannering, F., & Rutherford, S. (1999) “Evaluating Effects of Transportation Demand Management Strategies on Trip Generation by Using Poisson and Negative Binomial Regression.” Journal of the Transportation Research Board. Vol. 1682.
Yao, B., Yan, Q., Chen, Q., Tian, Z., & Zhu, X. (2018) “Simulation-based optimization for urban transportation demand management strategy.” Simulation. 94:7.
