Optimizing Sustainable Transportation Strategies for University Environments The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Hammer, Benjamin. 2018. Optimizing Sustainable Transportation Strategies for University Environments. Master's thesis, Harvard Extension School. Citable link https://nrs.harvard.edu/URN-3:HUL.INSTREPOS:37365422 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA Optimizing Sustainable Transportation Strategies for University Environments Benjamin A. Hammer A Thesis in the field of Sustainability for the Degree of Master of Liberal Arts in Extension Studies Harvard University June 2018 i Abstract This project explores strategies for improving university sustainable transportation efforts by exploring modal outcomes of Boston area university Transportation Demand Management (TDM) investments. TDM programs are a critical strategy employed by universities to reduce greenhouse gas emissions and traffic congestion, and to promote sustainable transportation modes. University TDM implementation has rapidly increased in the 21st century, yet both policies and outcomes vary significantly. With a variety of tools and strategies employed by university TDM practitioners, it is crucial to assess these strategies and outcomes to optimize investments given university resource constraints. This study builds on the extensive research of employer-based TDM practices, by exploring the pricing factors influencing modal outcomes of university-based TDM strategies. Using a twelve-year commute mode data set compiled through the Massachusetts Rideshare Regulation along with pricing structures of institutional parking facilities and details on transit subsidies or lack thereof, I explore the hypothesis that university investments in TDM programs are correlated with decreases in single occupant vehicle (SOV) commute modes, and that among those investments, pricing structures are the most significant predictor of SOV reductions. Pearson product-moment correlation coefficient analysis revealed insignificant correlations between institutional pricing variables, and sample variance of assembled university mode data revealed a substantial range in data quality. I conclude by ii discussing the possible reasons for this inconclusiveness, and suggest ways to reform the Rideshare Regulation process. iii Acknowledgements Thank you to Mark Rabinsky for his generous guidance and patience throughout the process. Without your mentorship and support this would not be possible. Thank you to Walter Hope, the Public Records Coordinator at the Massachusetts Department of Environmental Protection Bureau of Air and Waste, for putting up with my numerous data requests and methodological questions. Thank you to Phil Winters, the Transportation Demand Management Program Director at the University of South Florida Center for Urban Transportation Research, for helping put my research in context, and for providing invaluable insight regarding peer institutions and their expected survey outcomes. Thank you to the research consultants at the Harvard University Institute for Quantitative Social Science for exploring my data with me and helping me determine appropriate analytical tools and methods. iv Table of Contents Abstract ............................................................................................................................... ii Acknowledgements ............................................................................................................ iv Table of Contents ................................................................................................................ v List of Abbreviations ....................................................................................................... viii List of Tables ..................................................................................................................... ix List of Figures ..................................................................................................................... x I. Introduction ................................................................................................................. 1 Research Significance and Objectives ......................................................................... 1 Background .................................................................................................................. 2 Universities as Sustainable Transportation Ecosystems ................................... 3 Travel Behavior Influences and Planning Strategies ........................................ 3 Employer TDM Strategies ................................................................................ 4 Boston Metropolitan Region Transportation Amenities ................................... 6 TDM Modeling and Outcomes ......................................................................... 8 University TDM Strategies ............................................................................... 9 University TDM Vectors ................................................................................ 11 University TDM Pricing Structures and Subsidies ......................................... 13 TDM Dynamics of Study Universities ........................................................... 15 v Institutional Population and Transportation Dynamics .................................. 18 Boston University ............................................................................. 18 Boston College .................................................................................. 19 Massachusetts Institute of Technology ............................................. 19 Harvard University............................................................................ 20 Northeastern University .................................................................... 22 University of Massachusetts Boston ................................................. 22 Trip Reduction Ordinances ............................................................................. 23 Research Questions, Hypothesis and Specific Aims ................................................ 25 Hypothesis....................................................................................................... 26 Specific Aims .................................................................................................. 26 II. Methods .................................................................................................................... 28 Metrics & Data Collection .............................................................................. 28 Data Collection ............................................................................................... 29 III. Results ..................................................................................................................... 38 Arithmetic Mean ............................................................................................. 38 Institutional SOV Change Relative to Demographic Trends .......................... 38 vi Pearson Product-moment Correlation Coefficient .......................................... 39 Correlation Between MBTA Costs and SOV Rates ....................................... 40 Correlation Between Annual Parking Costs and SOV Rates .......................... 41 Correlation Between the Difference of MBTA and Parking Costs, and SOV Rates ................................................................................................................ 42 Population and Sampling Discrepancies ......................................................... 43 Data Variation ................................................................................................. 45 IV. Discussion ............................................................................................................... 48 SOV Rate Reduction Due to University Investments Hypothesis .................. 48 Pricing Structures as a Critical TDM Element Hypothesis ............................ 49 Data Challenges .............................................................................................. 52 Research Limitations and Caveats ............................................................................ 55 Questions for Further Research ................................................................................ 57 References ......................................................................................................................... 60 vii List of Abbreviations ACT Association for Commuter Transportation BC Boston College BU Boston University CUTR Center for Urban Transportation Research DEP Department of Environmental Protection MassDEP Massachusetts Department of Environmental Protection MassDOT Massachusetts Department of Transportation MBTA Massachusetts Bay Transit Authority MIT Massachusetts Institute of Technology MPO Metropolitan Planning Organization SOV Single Occupant Vehicle TDM Transportation Demand Management TMO Transportation Management Organization TRO Trip Reduction Ordinance UMass University of Massachusetts viii List of Tables Table 1. Factors Influencing SOV Rate in University Environments ............................. 12 Table 2. Institution Population