Estimating the potential for mode shift based on price and incentives
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The document discusses estimating potential shifts in transportation modes based on pricing and incentives at a campus, utilizing data from a 2012 travel survey. Key findings highlight that certain incentives, such as financial rewards and adjustments to parking costs, can effectively encourage mode shifts from driving to alternative transportation methods. Ongoing research aims to explore the intersection of economic and social incentives in shaping commuting behaviors.
Estimating the potential for mode shift based on price and incentives
- 1. BREAKING THE MODE estimating the potential for mode shift based on price and incentives William (Billy) Riggs, Jessica Kuo, & Elizabeth Deakin July 2013 William Riggs, PhD, AICP, LEED AP 1
- 2. Background: 2012 Travel Survey (~20% RR) Bike, 11.0% Drive Alone, 43.5% Carpool, 11.4% Transit, 23.9% Walk, 9.3% Other, 1.9% Faculty % Staff % TOTAL % Bike 114 19.6 171 8.6 285 11 Drive Alone 227 39 897 44.9 1124 43.5 Carpool 47 8.1 247 12.4 294 11.4 Transit 101 17.3 489 24.5 590 23.9 Walk 84 14.4 156 7.8 240 9.3 Other 9 1.5 40 2 49 1.9 582 100 2000 100 2582 100 Undergrad Student % Graduate Student % TOTAL % Bike 56 5.7 333 25 389 16.8 Drive Alone 41 4.1 99 7.4 140 6 Carpool 6 0.6 30 2.3 36 1.6 Transit 104 10.5 413 31.1 517 22.3 Walk 779 78.6 441 33.2 1220 52.6 Other 5 0.5 14 1.1 19 0.8 991 100 1330 100 2321 100 Faculty - Staff Primary Mode Student - Primary Mode Bike, 16.8% Drive Alone, 6.0% Carpool, 1.6% Transit, 22.3% Walk, 52.6% Other, 0.8% July 2013 William Riggs, PhD, AICP, LEED AP 2
- 3. July 2013 William Riggs, PhD, AICP, LEED AP 3
- 4. Potential to focus on other lots (blue) for study of off-street utilization July 2013 William Riggs, PhD, AICP, LEED AP 4
- 5. At the same time… a land use issue L1: “F” Permits L2: “C” Permits L3: “F” Permits 331 marked & stacked spaces July 2013 William Riggs, PhD, AICP, LEED AP 5
- 6. Background: Knowing the Environment Thought Digital Tools July 2013 William Riggs, PhD, AICP, LEED AP 6
- 7. Background: Knowing & Responding 7July 2013 William Riggs, PhD, AICP, LEED AP
- 8. Key Questions Can we estimate the potential for mode shift in campus travel behavior? Can we judge the cost effectivness of various strategies and estiamte GHG savings? Outline Theory Methods Results Further Questions Key Questions & Outline July 2013 William Riggs, PhD, AICP, LEED AP 8
- 9. Theory: Behavior & Environment 1. Nudge Research 2. Information 2. Pricing 3. Incentives • Providing better information can lead to different decisions (Ariely, 2010) • Social and market incentives drive decisions (Walker, 2012) • Many programs do not account for daily user decisions, length of trip or (if driving) the amount / cost of time (TCRP 2005; Litman 2006). • Dynamic (digital) information can lead to improved efficiency in these areas (Sengumta, 2012 July 2013 William Riggs, PhD, AICP, LEED AP 9
- 10. Literature Review Pull together Suite of potential TDM tools Gather elasticities for mode shift Stated Preference Survey 3000+ Faculty & Staff 22% Response Rate, Sig @ 95 C.I. Model potential results Linear Regression of most effective tools Life Cycle cost of potential savings / costs Environmental savings / costs Methods July 2013 William Riggs, PhD, AICP, LEED AP 10
- 11. 11 Significant Incentives (-) A free or less expensive bus pass*** (-) A financial reward (+) Cost of parking*** (+) Cost of driving to work*** (-) Inconvenience of parking*** (-) 24 hr service * (+) Nothing*** (+) Already ride*** (+) More security patrols*** (+) Commute club*** Insignificant Incentives (-) A free BART (regional rail) pass (-) Avoid traffic (+) More bus service (-) More passenger amenities (-) More on time performance (+) Easier pre-tax capability (+) Cleaner / newer buses Drive Less R2= .214 | Adj. R2= .206 Statistical significance: *** (p < 0.05) ** (0.05 < p < 0.10) * (0.10 < p < 0.20) Regression Results: Most Effective Incentives to Drive Less (N = 2,343) Key Potential Finding: Stick mightier than the carrot? Or, if you build it they will come and they will pay? Financial reward and potential freebies may work better in tandem with service improvements and making parking less available.
- 12. 12 Results: Estimating GHG (Responding to the Environment July 2013 William Riggs, PhD, AICP, LEED AP
- 13. What is the influence of price and how does it work with non-economic incentives and technology? Is there more than can be done in the arena of social incentives and marketing / education to ‘soft sell’ individuals to change the way they commute? Continued Questions July 2013 William Riggs, PhD, AICP, LEED AP 13
- 14. 14 Continuing Work: Variable Price and Technology – Dynamic Between Social & Economic Incentives • New Policies – Real-time Occupancy/ Sensors • Mobile phone / web availability • Future wayfinding signage opportunities • DTo match daily transportation decisions – Combine with new technology – Incentives for transit (free transit pass) – Price variable based on • location / proximity • time of day / day of week July 2013 William Riggs, PhD, AICP, LEED AP
- 15. Continuing Work: Education / Marketing Research July 2013 William Riggs, PhD, AICP, LEED AP 15
- 16. Continuing Work: Education / Marketing Research July 2013 William Riggs, PhD, AICP, LEED AP 16
- 17. Continuing Work: Education / Marketing Research July 2013 William Riggs, PhD, AICP, LEED AP 17
- 18. Questions / Comments William (Billy) Riggs, PhD AICP Assistant Professor, CalPoly San Luis Obispo wriggs@calpoly.edu / 805.756.6317 July 2013 William Riggs, PhD, AICP, LEED AP 18
Editor's Notes
- #2: Disclaimer – this may leave you unsatisfied as it is an unfinished work… ongoing sponsored by a FHWA, UC Berkeley Green Initiative Fund and P&T. As with any good research generates more and more questions… By campus off-street parking, I mean garages and lots – all through the hours of the day. And what do I mean by soft sells?
- #3: Overview --- Berkeley is sustainable and yet not -- I like to call it the prius version of sustainability that is somewhat self-righteous Only 26% of campus commuters (including students/staff/faculty) drive alone. 67% walk, bike take transit or campus shuttles. Total sample was roughly 23,000
- #4: By walking distance; Campus PTDM Master Plan inidcates spaces available
- #5: Campus PTDM Master Plan also shows spot shortages…
- #6: Net loss of ~290 spaces Will displace approximately 350 autos from the campus system
- #7: At the same time we have seen a revolutions in new was that people can both 1) know and 2) respond to the environment
- #9: https://www.youtube.com/watch?v=CElngLAjMaA 445
- #11: https://www.youtube.com/watch?v=CElngLAjMaA 445
- #12: As seen in Table 10, similar relationships appear in the full model as compared to more limited models. Again, there is a concave curve relationship with regard to age (which could indicate that older adults are more likely to live in more walkable locations) and housing attributes maintain their importance in explaining variation in walkability. When variables that influence travel, like vehicle ownership levels and proximity transit enter the model with individual factors, they improve the predictive capability over the limited model based on the improved F-statistic, which improves by 151.991.78 when 11 degrees of freedom are added [critical values of roughly 19 ( =.05) and 21 ( = .01)].
- #13: This memo is in response to your 22 September 2010 email requesting a quantitative snapshot of the potential greenhouse gas (GHG) reductions from our proposed Climate-Smart Parking program. The program could save 605,524 gallons of gasoline and yield a climate benefit of 5,383 metric tons of CO2 per year. According to the EPA 7, this equates to the CO2 emissions from 12,519 barrels of oil consumed, the electricity use of 653 homes for one year, or the carbon sequestered by 138,028 tree seedlings grown for 10 years. It does not include the time and mobility benefits gained as a part of the project, or the savings from the numerous visitors the campus serves each day. A table that outlines these reductions can be seen below. 1. BearPass program includes only trips related to faculty and staff; wayfinding program includes trips for students, faculty and staff. 2. Trips in excess of 2,677 (half of peak utilization) are eligible circling trips; yielding 8,701 trips to campus that involve a hunt for parking. This does not include campus visitors averaging ~400 / day. Circling factor based on the average VMT from four (4) common circling routes. See Attachment 1 for more details. 3. Average round trip is approximately 23.84 miles based on 2008-2009 Transportation Surveys. 4. Potential VMT reductions from BearPass assume an elasticity of -0.3 based on numerous publications; wayfinding program assumes that 90% of circling trips are mitigated. 5. Average fuel efficiency standard of 22.1 miles/gallon based on 2005 Bureau of Transportation Statistics Data which is consistent with the verified UC Berkeley GHG inventory. Cost savings based on the 2009 IRS standard mileage rate of $0.55 / mile. 6. GHG reductions assume unleaded fuel, 19.4 pounds of CO2 / gallon based and 8.89*10^3 metric tons CO2/gallon of gasoline on EPA standards (http://www.epa.gov/oms/climate/420f05001.htm ; http://www.epa.gov/cleanenergy/energy-resources/refs.html) 7. http://www.epa.gov/cleanenergy/energy-resources/calculator.html
- #14: https://www.youtube.com/watch?v=CElngLAjMaA 445
- #15: Parking Access and Revenue Control System Gated Access Payment and Occupancy Data Parking Guidance and Information Systems Real-time availability - Cell phone / 511
- #17: Soft-sell for pledges: 20 sign-ups We had great turnout at the event and 22 people signed up to break the mode for custom trip planning assistance. We had about 5 onsite signups for the BearPass (I think that’s right but I didn’t get the final number from Devika). We also had a few cyclists and transit riders who saw or heard about the event from friends and expressed interest in the trip planning services -- so it could be that there is a lot of latent demand for help with trip planning (Note: we only invited those who were documented as parking in UHall during our surveys.)
- #18: Hand-delivered
- #19: Disclaimer – this may leave you unsatisfied as it is an unfinished work… ongoing sponsored by a FHWA, UC Berkeley Green Initiative Fund and P&T. As with any good research generates more and more questions… By campus off-street parking, I mean garages and lots – all through the hours of the day. And what do I mean by soft sells?